Look ahead of links/alter links

ABSTRACT

A computationally-implemented method comprising retrieving at least a portion of data from a data source, determining an effect of the data, determining an acceptability of the effect of the data at least in part via a virtual machine representation of at least a part of a real machine having one or more end-user specified preferences and providing at least one data display option based on the determining acceptability of the effect of the data.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to and claims the benefit of theearliest available effective filing date(s) from the following listedapplication(s) (the “Related Applications”) (e.g., claims earliestavailable priority dates for other than provisional patent applicationsor claims benefits under 35 USC §119(e) for provisional patentapplications, for any and all parent, grandparent, great-grandparent,etc. applications of the Related Application(s)).

RELATED APPLICATIONS

-   -   1. For purposes of the USPTO extra-statutory requirements, the        present application constitutes a continuation-in-part of U.S.        patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS,        naming Gary W. Flake; William H. Gates, III; Roderick A. Hyde;        Edward K. Y. Jung; Royce A. Levien; Robert W. Lord; Mark A.        Malamud; Richard F. Rashid; John D. Rinaldo, Jr.; Clarence T.        Tegreene; Charles Whitmer; and Lowell L. Wood, Jr. as inventors,        filed 21 Dec. 2007, application Ser. No. 12/005,064 now        abandoned, or is an application of which a currently co-pending        application is entitled to the benefit of the filing date.    -   2. For purposes of the USPTO extra-statutory requirements, the        present application constitutes a continuation-in-part of U.S.        patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS,        naming Gary W. Flake; William H. Gates, III; Roderick A. Hyde;        Edward K. Y. Jung; Royce A. Levien; Robert W. Lord; Mark A.        Malamud; Richard F. Rashid; John D. Rinaldo, Jr.; Clarence T.        Tegreene; Charles Whitmer; and Lowell L. Wood, Jr. as inventors,        filed Dec. 27, 2007, application Ser. No. 12/005,637 now        abandoned, or is an application of which a currently co-pending        application is entitled to the benefit of the filing date.    -   3. For purposes of the USPTO extra-statutory requirements, the        present application constitutes a continuation-in-part of U.S.        patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS,        naming Gary W. Flake; William H. Gates, III; Roderick A. Hyde;        Edward K. Y. Jung; Royce A. Levien; Robert W. Lord; Mark A.        Malamud; Richard F. Rashid; John D. Rinaldo, Jr.; Clarence T.        Tegreene; Charles Whitmer; and Lowell L. Wood, Jr. as inventors,        filed Mar. 6, 2008, application Ser. No. 12/074,855, which is        currently co-pending, or is an application of which a currently        co-pending application is entitled to the benefit of the filing        date.    -   4. For purposes of the USPTO extra-statutory requirements, the        present application constitutes a continuation-in-part of U.S.        patent application entitled LOOK AHEAD OF LINKS/ALTER LINKS,        naming Gary W. Flake; William H. Gates, III; Roderick A. Hyde;        Edward K. Y. Jung; Royce A. Levien; Robert W. Lord; Mark A.        Malamud; Richard F. Rashid; John D. Rinaldo, Jr.; Clarence T.        Tegreene; Charles Whitmer; and Lowell L. Wood, Jr. as inventors,        filed May 20, 2008, Ser. No. 12/154,148, which is currently        co-pending, or is an application of which a currently co-pending        application is entitled to the benefit of the filing date.

The United States Patent Office (USPTO) has published a notice to theeffect that the USPTO's computer programs require that patent applicantsreference both a serial number and indicate whether an application is acontinuation or continuation-in-part. Stephen G. Kunin, Benefit ofPrior-Filed Application, USPTO Official Gazette Mar. 18, 2003, availableat http://www.uspto.gov/web/offices/com/sol/og/2003/week11/patbene.htm.The present Applicant has provided above a specific reference to theapplication(s) from which priority is being claimed as recited bystatute. Applicant understands that the statute is unambiguous in itsspecific reference language and does not require either a serial numberor any characterization, such as “continuation” or“continuation-in-part,” for claiming priority to U.S. patentapplications. Notwithstanding the foregoing, Applicant understands thatthe USPTO's computer programs have certain data entry requirements, andhence Applicant is designating the present application as acontinuation-in-part of its parent applications as set forth above, butexpressly points out that such designations are not to be construed inany way as any type of commentary and/or admission as to whether or notthe present application contains any new matter in addition to thematter of its parent application(s).

All subject matter of the Related Application and of any and all parent,grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

BACKGROUND

Web sites often contain links to other web sites enabling a user tonavigate from one web site to another. Certain links may contain datathat may compromise security and/or privacy. Certain links may containdata that a user may not desire to view.

SUMMARY

A computationally implemented method includes, but is not limited to:retrieving at least a portion of data from a data source; determining acontent of the data; determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences; and providing at least one data displayoption based on the determining acceptability of the effect of thecontent of the data. In addition to the foregoing, other computationallyimplemented method aspects are described in the claims, drawings, andtext forming a part of the present disclosure.

In one or more various aspects, related systems include but are notlimited to circuitry and/or programming for effecting theherein-referenced method aspects; the circuitry and/or programming canbe virtually any combination of hardware, software, and/or firmwareconfigured to effect the herein- referenced method aspects dependingupon the design choices of the system designer.

A computationally implemented system includes, but is not limited to:means for retrieving at least a portion of data from a data source;means for determining a content of the data; means for determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a part of a realmachine having one or more end-user specified preferences; and means forproviding at least one data display option based on the determiningacceptability of the effect of the content of the data. In addition tothe foregoing, other system aspects are described in the claims,drawings, and text forming a part of the present disclosure.

A computationally implemented system includes, but is not limited to:circuitry for retrieving at least a portion of data from a data source;circuitry for determining a content of the data; circuitry fordetermining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation of at least a part ofa real machine having one or more end-user specified preferences; andcircuitry for providing at least one data display option based on thedetermining acceptability of the effect of the content of the data. Inaddition to the foregoing, other system aspects are described in theclaims, drawings, and text forming a part of the present disclosure.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A illustrates an exemplary environment in which one or moretechnologies may be implemented.

FIG. 1B illustrates an operational view of a real machine in which atleast a portion of the system illustrated in FIG. 1A has beenimplemented.

FIG. 1C illustrates an operational view of a real machine in which atleast a portion of the system illustrated in FIG. 1A has beenimplemented.

FIG. 1D illustrates an operational view of a real machine in which atleast a portion of the system illustrated in FIG. 1A has beenimplemented.

FIG. 2 illustrates an operational flow representing example operationsrelated to providing acceptable data content to a real machine.

FIG. 3 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 4 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 5 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 6 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 7 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 8 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 9 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 10 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 11 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 12 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 13 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 14 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 15 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 16 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 17 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 18 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 19 illustrates an alternative embodiment of the operational flow ofFIG.2.

FIG. 20 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 21 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 22 illustrates an alternative embodiment of the operational flow ofFIG. 2.

FIG. 23 illustrates an alternative embodiment of the operational flow ofFIG. 2.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here. Referring to FIG. 1A, a system 100 related to lookingahead for data is illustrated. The system 100 may include a dataretriever engine 102, a data content determination engine 104, an Effectof content acceptability determination engine 106, and a data providerengine 108. Data content determination engine 104 may include a databaseexamination engine 112, a data traverser engine 114, and a local dataexamination engine 116. Effect of content acceptability determinationengine 106 may include a virtual machine module 118 including one ormore virtual machines 11, 12, and 13 and a user preference database 120.Data content provider engine 108 may include a data modification engine122 that may further include a data obfuscation engine 124 and a dataanonymization engine 126. Data content provider engine 108 may alsoinclude a data redirection engine 128.

FIG. 1B shows an operational view of real machine 130 (e.g., a desktop,notebook, or other type computing system, including or excluding one ormore peripheral devices) in which at least a portion of system 100 (FIG.1A) has been implemented. In some instances, system 100 is at leastpartially implemented in a single core processor at least partiallyresident within real machine 130 (e.g., one or more virtual machines ofvirtual machine module 118 at least partially implemented on asingle-core processor of real machine 130). In other instances, system100 is at least partially implemented in a multi-core processor at leastpartially resident within real machine 130 (e.g., one or more virtualmachines of virtual machine module 118 at least partially respectivelyimplemented on one or more cores of a multi-core processor of realmachine 130). In other instances, system 100 is at least partiallyimplemented in a single-core processor at least partially non-residentwithin real machine 130 (e.g., one or more virtual machines of virtualmachine module 118 at least partially implemented on a single-coreprocessor of a hosting site/machine/system physically distal from realmachine 130). In other instances, system 100 is at least partiallyimplemented in a multi-core processor at least partially non-residentwithin real machine 130 (e.g., one or more virtual machines of virtualmachine module 118 at least partially respectively implemented on one ormore cores of a multi-core processor of a hosting site/machine/systemphysically distal from real machine 130).

FIG. 1B depicts real machine 130 containing data 110 (e.g., a Web page)containing Link 1, Link 2, and Link 3. FIG. 1B illustrates an example inwhich at least a part of system 100 traverses Link 1, Link 2, and Link 3of data 110 via virtual machine representations of real machine 130. Insome instances, such virtual machine traversals are utilized toprospectively determine what might happen should real machine 130 beused to traverse such links. For example, determining how suchtraversal(s) might compare to one or more user-associated preferences ofreal machine 130 (e.g., that user 10 prefers to visit sites havingcontent acceptable to a defined organization, such a government; thatuser 10 prefers not to visit sites having malware or spyware; that user10 prefers not to visit sites that reset real machine hardware options(e.g., audio/visual peripherals); that user 10 prefers not to visitsites that reset real machine software options (e.g., proxy servers);etc.). User-associated preferences of real machine 130 may be stored inuser preference database 120 (FIG. 1A) of Effect of contentacceptability determination engine 106 (FIG. 1A). User preferencedatabase 120 may contain user preferences with respect to content of thereal machine 130, hardware of the real machine 130, software of the realmachine 130 and an operating system of the real machine. User preferencedatabase 120 may be in communication with virtual machine module 118(FIG. 1A). Specifically, virtual machine module 118 (FIG. 1A) mayreceive user preference database information from user preferencedatabase 120 (FIG. 1A) and spawn a copy of at least a portion of userpreference database 120 (FIG. 1A) on each of virtual machines 11, 12and/or 13.

FIG. 1B illustrates virtual machine 11. Virtual machine 11 may beillustrated as included in virtual machine module 118 (FIG. 1A) ofEffect of content acceptability determination engine 106 (FIG. 1A). FIG.1B shows virtual machine 11 encompassing a virtual machinerepresentation of real machine 130, post (e.g. subsequent to) activationof Link 1 (e.g., as at least a part of real machine 130 would exist hadlink 1 actually been traversed on real machine 130). FIG. 1B depictsvirtual machine 11 including a virtual machine representation of thecontent of the real machine 130 post activation of Link 1. Examples ofsuch content include a movie, music file, a script (e.g., Java script orActive X control), a markup language, an email, etc. downloaded ontoreal machine 130 from one or more sources associated withactivation/traversal of Link 1.

FIG. 1B also illustrates virtual machine 11 including a virtual machinerepresentation of software (e.g., a state of software) of the realmachine 130 post (e.g. subsequent to) activation of Link 1. Examples ofsuch software might include a commercial word processing program orsuite of programs (e.g. Microsoft® Office for Windows), an open sourceWeb browser (e.g., Mozilla's Firefox® Browser), an AJAX mash up (e.g.,an executing JavaScript™ and/or data retrieved by same via an XML-likescheme), or a commercial database management system (e.g., one or moreof Oracle Corporation's various products), a commercialanti-malware/spyware programs (e.g., such as those of SymantecCorporation or McAfee,Inc.), etc.

FIG. 1B also illustrates virtual machine 11 including a virtual machinerepresentation of hardware (e.g. a state of the hardware) of the realmachine 130 post activation of Link 1. Examples of such hardware mightinclude all or part of a chipset (e.g., data processor and/or graphicsprocessor chipsets such as those of Intel Corporation and/orNvidiaCorporation), a memory chip (e.g., flash memory and/or randomaccess memories such as those of Sandisk Corporation and/or SamsungElectronics, Co., LTD), a data bus, a hard disk (e.g., such as those ofSeagate Technology, LLC), a network adapter (e.g., wireless and/or wiredLAN adapters such as those of Linksys and/or CiscoTechnology, Inc.),printer, a removable drive (e.g., flash drive), a cell phone, etc.

FIG. 1B also illustrates virtual machine 11 including a virtual machinerepresentation of an operating system (e.g., a state of an operatingsystem and/or network operating system) of the real machine 130 postactivation of Link 1. Examples of such an operating system might includea computer operating system (e.g., e.g. Microsoft® Windows 2000, Unix,Linux, etc) and/or a network operating system (e.g., the InternetOperating System available from Cisco Technology, Inc. Netware®available from Novell, Inc., and/or Solaris available from SunMicrosystems, Inc.).

FIG. 1B also illustrates that virtual machine 11 may run on core 11 of amulti-core processor. In addition to the herein, those skilled in theart will appreciate that the virtual machine representations discussedherein are not limited to specific examples described, but insteadinclude any components of real machine 130 as such might be understoodin the art. Examples of the foregoing would include firmware, logicassociated with display units, logic associated with robotics,application specific integrated circuits, etc.

As noted, in some instances system 100 may traverse (e.g. view) links ofdata 110 via one or virtual machine representations of at least a partof real machine 130. Accordingly, FIG. 1B shows virtual machine 12encompassing a virtual machine representation of real machine 130 (e.g.,one or more states of one or more components associated with realmachine 130), post activation of Link 2. FIG. 1B depicts virtual machine12 at least partly running on core 12 of a multi-core processor. Virtualmachine module 118 (FIG. 1A) of Effect of content acceptabilitydetermination engine 106 (FIG. 1A) may be illustrated to include virtualmachine 12.

FIG. 1B also illustrates virtual machine 12 may include a virtualmachine representation of content (e.g. a video) of real machine 130post activation of Link 2, a virtual machine representation of software(e.g. Microsoft Office for Windows) of real machine 130 post activationof Link 2, a virtual machine representation of hardware (e.g. thecircuitry or processor of the real machine) of real machine 130 postactivation of Link 2, and a virtual machine representation of operatingsystem (e.g. Microsoft Windows 2000, XP, Vista) of real machine 130 postactivation of Link 2.

As noted, in some instances system 100 may traverse links of data 110via one or more virtual machine representations of at least a part ofreal machine 130. Accordingly, FIG. 1B shows virtual machine 13encompassing a virtual machine representation of real machine 130, postactivation of Link 3 (e.g., representative of one or more states of oneor more hardware/software/firmware components of/resident within realmachine 130). The foregoing constitutes one example of how system 100may use virtual machine 13 to traverse Link 3 (e.g. a link relating to alist of or links to information on architectural building styles).Virtual machine module 118 (FIG. 1A) of Effect of content acceptabilitydetermination engine 106 (FIG. 1A) may include virtual machine 13. FIG.1B further illustrates virtual machine 13 may include a virtual machinerepresentation of the content (e.g. a markup language) of the realmachine 130 post activation of Link 3, a virtual machine representationof the software (e.g. Unix) of the real machine 130 post activation ofLink 3, a virtual machine representation of the hardware (e.g. a harddisk) of the real machine 130 post activation of Link 3, and a virtualmachine representation of the operating system (e.g. Solaris OperatingSystem) of the real machine 130 post activation of Link 3. FIG. 1B showsthat virtual machine 13 may be run on core 13 of a multi-core processor.

Upon traversal of links 1, 2, and 3 by virtual machines 11, 12, and 13,respectively, each of virtual machines 11, 12, and 13 may determinewhether an effect of the data content is acceptable to a user based on auser's preferences. Virtual machines 11, 12 and/or 13 may compare thetraversed data to one or more user preferences stored in a userpreference database 120 (FIG. 1A). User preference database informationmay be communicated to virtual machine module 118 (FIG. 1A) and a copyof at least a portion of user preference database 120 may be spawned(e.g. generated) on each virtual machines 11, 12 and/or 13. Virtualmachines 11, 12, and 13 may communicate the results of a respectivecomparison of activation of a link (e.g. loading at least a portion of alink's content onto a virtual machine 11, 12 and/or 13) to a userpreference (e.g. a preference not to load malware onto a user's realmachine) to virtual machine module 118 (FIG. 1A). Virtual machine module118 (FIG. 1A) may communicate the results of a comparison of activationof a link to a user preference to effect of content acceptabilitydetermination engine 106 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may communicate the comparison to the datacontent provider engine 108 (FIG. 1A). The data content provider engine108 may then provide the results (e.g. one or more weblinks approved forviewing) to a real machine 130 (e.g. a computing device with or withoutassociated peripherals) that may be viewable to a user 10 on a display.

FIG. 1C shows a partial follow-on operational view of real machine 130(e.g., a desktop, notebook, or other type computing system) in which atleast a portion of system 100 (FIG. 1A) has been implemented (e.g., afollow-on operational view of the systems/methods illustrated as in FIG.1B). Specifically, FIG. 1C shows a drill-down view of an example of thevirtual machine 11 including a virtual machine representation of thecontent of the real machine 130 post activation of Link 1 (e.g., adrill-down on the systems/methods shown/described in relation to FIG.1B). In this drill down example, depicted is the virtual machinerepresentation of the content of the real machine 130 post activation ofLink 1. In the example shown, the content is depicted as data 110 havingLink 4, Link 5 and Link 6. As a specific example, data 110 could be aWeb page containing embedded Link 4 to an advertisement, Link 5 to avideo file, and Link 6 to a still image file.

In some instances, system 100 may use additional virtual machinerepresentations of at least a part of real machine 130 to prospectivelytraverse Link 4, Link 5, and Link 6. Accordingly, FIG. 1C illustratessystem 100 generating virtual machine representations of real machine130, used to traverse Links 4, 5, and 6, in the context of virtualmachines 21, 22, and 23, respectively. Those skilled in the art willthus appreciate that, in the example shown in FIG. 1C, system 100 iscreating second-order virtual machine representations to prospectivelyinvestigate the effects on the states of various components of realmachine 130 via sequential traversals of links. That is, the virtualmachine representations of real machine 130 encompassed in virtualmachine 21, virtual machine 22, and virtual machine 23 of FIG. 1C aregenerated by system 100 based on the first-order virtual machinerepresentation of virtual machine 11 as shown/described in relation toFIG. 1B.

Upon traversal of links 4, 5, and 6 by virtual machines 21, 22, and 23,respectively, each of virtual machines 21, 22, and 23 may determinewhether an effect of the data content is acceptable to a user based on auser's preferences. Virtual machines 21, 22, and 23 may compare thetraversed data to one or more user preferences stored in a userpreference database 120 (FIG. 1A). As previously described, userpreference database information may be communicated to virtual machinemodule 118 (FIG. 1A) and a copy of at least a portion of user preferencedatabase 120 may be spawned (e.g. generated) on each virtual machines11, 12 and/or 13. Virtual machine 11 may then communicate userpreference database information to each of virtual machines 21, 22, and23, and a copy of a user preference database 120 (FIG. 1A) may bespawned on each of virtual machines 21, 22, and 23. Virtual machines 21,22, and 23 may communicate the results of a respective comparison ofactivation of a link (e.g. loading at least a portion of a link'scontent onto a virtual machine 21, 22, and/or 23) to a user preference(e.g. a preference to prevent installation of a rootkit onto a user'sreal machine) to virtual machine 11. Virtual machine 11 may communicatethe results of a comparison to virtual machine module 118 (FIG. 1A).Virtual machine module 118 (FIG. 1A) may communicate the results of acomparison of activation of a link to a user preference to effect ofcontent acceptability determination engine 106 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may communicate thecomparison to the data content provider engine 108 (FIG. 1A). The datacontent provider engine 108 may then provide the results (e.g. one ormore weblinks approved for viewing) to a real machine 130 (e.g. acomputing device with or without associated peripherals) that may beviewable to a user 10 on a display.

FIG. 1C shows virtual machine 21 encompassing a virtual machinerepresentation of real machine 130 post (e.g. subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 4(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 21 may be run on core 31 of a multi-core processor. FIG.iC depicts system 100 traversing Link 4 via a virtual machinerepresentation of real machine 130 encompassed within virtual machine21. Accordingly, FIG. 1C illustrates virtual machine 21 including avirtual machine representation of content (e.g., a movie, web page,music file, etc.) of the real machine 130 post sequential activation ofLink 1 then Link 4, a virtual machine representation of the software(e.g.) of the real machine 130 post sequential activation of Link 1 thenLink 4, a virtual machine representation of the hardware (e.g. thecircuitry or processor of the real machine) of the real machine 130 postsequential activation of Link 1 then Link 4, and a virtual machinerepresentation of the operating system (e.g. Linux) of the real machine130 post sequential activation of Link 1 then Link 4.

FIG. 1C shows virtual machine 22 encompassing a virtual machinerepresentation of real machine 130 post (e.g., subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 5(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 22 may be run on core 32 of a multi-core processor. FIG.1C depicts system 100 traversing Link 5 via a virtual machinerepresentation of real machine 130 encompassed within virtual machine22. Accordingly, FIG. 1C illustrates virtual machine 22 including avirtual machine representation of content (e.g. a graphical image, atext file, an email, etc) of the real machine 130 post (e.g., subsequentto) sequential activation of Link 1 then Link 5, a virtual machinerepresentation of software (e.g. an AJAX mashup) of the real machine 130post sequential activation of Link 1 then Link 5, a virtual machinerepresentation of hardware (e.g. a network adapter) of the real machine130 post sequential activation of Link 1 then Link 5, and a virtualmachine representation of an operating system (e.g. Mac OS/X) of thereal machine 130 post sequential activation of Link 1 then Link 5.

FIG. 1C shows virtual machine 23 may be a virtual machine representationof real machine 130 post (e.g., subsequent to) sequential activation ofLink 1 (e.g., FIG. 1B) then Link 6 (e.g., FIG. 1C). FIG. 1C depicts thatin one instance virtual machine 23 may be run on core 33 of a multi-coreprocessor. System 100 is shown using virtual machine 23 to traverse Link6. FIG. 1C further illustrates virtual machine 23 encompassing a virtualmachine representation of the content (e.g. a music file) of the realmachine 130 post sequential activation of Link 1 then Link 6, a virtualmachine representation of the software (e.g. a commercial databasemanagement system) of the real machine 130 post sequential activation ofLink 1 then Link 6, a virtual machine representation of the hardware(e.g. a removable drive) of the real machine 130 post sequentialactivation of Link 1 then Link 6, and a virtual machine representationof the operating system (e.g. GNU, Berkeley Software Distribution) ofthe real machine 130 post sequential activation of Link 1 then Link 6(e.g., as such might appear after activation of a link installed by arootkit via malware/spyware).

Those skilled in the art will appreciate that system 100 may generate asmany virtual machines as necessary to traverse individual links ofinterest, and that the examples herein are used for sake of clarity.Those skilled in the art will appreciate that examples used herein aremeant to be indicative of the fact that system 100 can run in whole orin part on proximate single or multi-core machines and/or distal singleor multi-core machines, on distributed computing systems (e.g., GRID orclustered), on local computing systems, or hosted computing systems,etc.

FIG. 1D shows a representative view of an implementation of real machine130 (e.g., a desktop, notebook, or other type computing system, and/orone or more peripheral devices). FIG. 1D illustrates thatimplementations of real machine 130 may include all/part of computingdevice 132 and/or all/part of one or one or more peripherals associatedcomputing device 132. The computing device 132 may be any device capableof processing one or more programming instructions. For example, thecomputing device 132 may be a desktop computer, a laptop computer, anotebook computer, a mobile phone, a personal digital assistant (PDA),combinations thereof, and/or other suitable computing devices.

As noted, in some instances, real machine 130 may also include at leasta portion of one or more peripheral devices connected/connectable (e.g.,via wired, waveguide, or wireless connections) to real machine 130.Peripheral devices may include one or more printers 134, one or more faxmachines 136, one or more peripheral memory devices 138 (e.g., flashdrive, memory stick), one or more network adapters 139 (e.g., wired orwireless network adapters), one or more music players 140, one or morecellular telephones 142, one or more data acquisition devices 144 (e.g.robots) and/or one or more device actuators 146 (e.g., an hydraulic arm,a radiation emitter, or any other component(s) of industrial/medicalsystems).

FIG. 2 illustrates an operational flow 200 representing exampleoperations related to FIGS. 1A, 1B, 1C and 1D. In FIG. 2 and infollowing figures that include various examples of operational flows,discussion and explanation may be provided with respect to theabove-described examples of FIGS. 1A, 1B, 1C, and 1D and/or with respectto other examples and contexts. However, it should be understood thatthe operational flows may be executed in a number of other environmentsand contexts, and/or in modified versions of FIGS. 1A, 1B, 1C, and 1D.Also, although the various operational flows are presented in thesequence(s) illustrated, it should be understood that the variousoperations may be performed in other orders than those which areillustrated, or may be performed concurrently.

After a start operation, the operational flow 200 shows operation 210,which depicts retrieving at least a portion of data from a data source(e.g. a computer accessible from the internet). For example, FIG. 1Ashows a data retriever engine 102. Data retriever engine may retrieve(e.g. download) data 110 (e.g. a web page) from a data source such as acomputer accessible from the internet. Specifically, data 110 may be webcontent retrieved from the world wide web via a computing deviceaccessible from the internet. For example, data retriever engine 102 mayset a URL and add a querystring value to the URL. Data retriever engine102 may then make a request to the URL and scan the response receivedfrom the URL. Data 110 may be a web site or web page containing one ormore links to additional web sites, such as shown, for example, in FIG.1B and/or FIG. 1C. Data 110 may in some instances be textual, atwo-dimensional or three-dimensional image, audible, or videorepresentations, which in some instances may entail programming codesuch as html, javascript, C, C++, or any other programming code capableof producing text, visual images, audio content, video content or anycombination of text, visual images, audible content and video content.

Then, operation 220 depicts determining a content of the data. FIG. 1Ashows a data content determination engine 104. Data contentdetermination engine 104 may determine the content (e.g. text, audio,video, etc.) of the data 110 retrieved from the data source by the dataretriever engine 102. For example, FIG. 1A shows that the data contentdetermination engine 104 may include a database examination engine 112,a data traverser engine 114, and a local data examination engine 116. Adatabase examination engine 112 may examine (e.g. scan) a database (e.g.information retrieved from a storage server) of known data (e.g.weblinks) and compare the known data to the data 110 to determine datacontent (e.g. data types such as text, image, audio and/or videocontent). Additionally, database examination engine 112 may compare aportion of data 110 (e.g. a data packet header) against a databaseincluding a collection of data broken down into its respectivecomponents (e.g. header, body). If the comparison yields a reasonablematch, the data type may be determined. Data content determination maybe transmitted from the database examination engine 112 to the datacontent determination engine 104.

A data traverser engine 114 may traverse (e.g. parse) at least a portionof the data (e.g. a portion of a web page) to determine data content(e.g. an image or video) within the portion of the data. Data traversalmay occur in real time (e.g. simultaneously as data is loading). Datacontent determination may be transmitted from the data traverser engine114 to the data content determination engine 104.

A local data examination engine 116 may locally (e.g. on the realmachine 130) examine (e.g. analyze) at least a portion of the data (e.g.data packets) to determine data content (e.g. an audio file). Forinstance, local data examination engine 116 may view an amount of htmlsource code to locate markers signifying the type of data content. Datacontent determination may be transmitted from the local data examinationengine 116 to the data content determination engine 104. Data contentdetermination engine 104 may transmit a data content determination tothe Effect of content acceptability determination engine 106. Thecontent of the data 110 may be any textual, audible, or visual contentloaded or displayed after the data is retrieved by the data retrieverengine 102. For instance, the content of the data 110 may be a web pagecomprising text, sound, and/or an image, a link to a web page, a videoor any combination of text, sound, images, links to web pages, andvideos.

Then, operation 230 illustrates determining an acceptability of aneffect of the content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences. FIG. 1A illustrates an Effect of contentacceptability determination engine 106. Effect of content acceptabilitydetermination engine 106 may receive data and an associated data contentdetermination (e.g. data is an audio file) from data contentdetermination engine 104 post retrieval of data by data retriever engine102 and transfer of retrieved data to data content determination engine106. Effect of content acceptability determination engine 106 (FIG. 1A)may utilize, for example, virtual machine 12 (FIG. 1A) spawned byvirtual machine module 118 to determine whether data associated withLink 2 would result in a change in the operating system of real machine130 contra to user preferences regarding the operating system asreflected by user preference database 120.

Then, operation 240 shows providing at least one data display optionbased on the determining acceptability of the effect of the content ofthe data. FIG. 1A illustrates a data provider engine 108. Data providerengine 108 may be in communication with Effect of content acceptabilitydetermination engine 106, which may receive data and an associated datacontent determination (e.g. data is a video file) from data contentdetermination engine 104 post retrieval of data by data retriever engine102 and transfer of retrieved data to data content determination engine104. Effect of content acceptability determination engine 106 maytransfer at least effect of content acceptability determination to thedata provider engine 108 to provide at least one data display option. Inone example, data provider engine 108 (FIG. 1A) provides data viaplacing the data on a visual display, where the content is such that itmeets one or more thresholds associated with the effect of contentacceptability determination. Provided data may be a list of web links, aweb page, or other data that either have been deemed acceptable byeffect of content acceptability determination engine 106 or that havebeen modified (e.g., obfuscated), such as by data modification engine122, such that the to-be-displayed content is judged acceptable underuser preferences. Provided data may be modified via the datamodification engine 122. For instance, provided data may be obfuscatedvia the data obfuscation engine 124 (e.g., at least a portion of thedisplayed data may be blurred out or disabled), or provided data may beanonymized via the data anonymization engine 126 (e.g., at least aportion of the data may be deleted entirely). Data content providerengine 108 (FIG. 1A) may receive at least one display instruction (e.g.OK to display links 1 and 2) from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A) for at least aportion of data to be displayed. For instance, each of virtual machines11, 12, and/or 13 may include one or more instruction generating modulesconfigured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a user preference stored in a copy of the userpreference database 120 (FIG. 1A) spawned on the virtual machine 11, 12,and/or 13. Such instruction may include an instruction to the datacontent provider engine 108 to prevent the data content provider engine108 from displaying data that may configure a hardware profile of realmachine 130 counter to anti-viral settings stored in the user preferencedatabase 120 (FIG. 1A), or an instruction to the data content providerengine 108 to prevent the data content provider engine 108 fromdisplaying data that may configure an operating system of real machine130 counter to a previous operating system of the real machine (130)(e.g. determine if a rootkit has been installed).

FIG. 3 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 3 illustrates example embodiments where theoperation 220 may include at least one additional operation. Additionaloperations may include an operation 302, an operation 304, and/or anoperation 306.

Operation 302 illustrates examining a database of known data for datainformation. Continuing the example above, data content determinationengine 104 (FIG. 1A) may receive data 110 retrieved from a data sourceby the data retriever engine 102 and communicate data 110 to thedatabase examination engine 112. Database examination engine 112 may beconfigured to examine a database of data provided, for example, by adata provider service or a database of data stored on a real machine130. For instance, a database may include a list of links viewed by auser or pre-approved by a user based on one or more user-specifiedpreferences, such as links from a specific source of information (e.g.,the Roman Catholic Church). Database examination engine 112 maycommunicate the results of a database examination to the data contentdetermination engine 104.

Operation 304 shows traversing data in real time. Continuing the exampleabove, database traverser engine 114 (FIG. 1A) examines data receivedfrom the data content engine 104 following retrieval of data from thedata retriever engine 102. Data traverser engine 114 may be configuredto scan the data 110 to determine a data content type (e.g. an image, avideo or an audio file). Database traverser engine 114 may communicatethe results of a data traversal to the data content determination engine104.

Operation 306 depicts locally examining data. For instance, continuingthe example above, data content determination engine 104 (FIG. 1A) mayreceive data 110 retrieved from a data source (e.g. a computeraccessible through the internet) by the data retriever engine 102 andcommunicate data 110 to the local data examination engine 116. The localexamination engine 116 may examine the data 110 on the real machine 130at the location of the real machine 130 (e.g. executed on a subsystemwithin the real machine) to determine a data content type (e.g. adownloadable software program). Local data examination engine 116 maycommunicate the results of a local data examination to the data contentdetermination engine 104.

FIG. 4 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 4 illustrates example embodiments where theoperation 230 may include at least one additional operation. Additionaloperations may include an operation 402, an operation 404, an operation406, an operation 408, and/or an operation 410.

Operation 402 illustrates determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences by issuing a request to a remote computerfor additional data information. Continuing the example above, FIG. 1Ashows the Effect of content acceptability determination engine 106.Effect of content acceptability determination engine 106 may receive adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B shows virtual machines 11, 12 and/or 13. Each of virtualmachines 11, 12, and/or 13 may examine (e.g. scan) at least a portion ofdata (e.g. an imbedded link on a webpage) to determine if the datareferences additional data (e.g. one or more additional links).Additional data may be a web page comprising text and/or an image, alink to a web page, a video or any combination of text, images, links toweb pages, or videos. Virtual machines 11, 12 and/or 13 may traverseadditional data to determine an acceptability of an effect of the datacontent. Effect of content acceptability determination may becommunicated to Effect of content acceptability determination engine 106(FIG. 1A) that may communicate an effect of content acceptabilitydetermination to a data provider engine 108 (FIG. 1A).

Further, operation 404 shows determining an acceptability of an effectof the content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences by determining whether data referencesadditional data when loading. Continuing the example above, FIG. 1Ashows the Effect of content acceptability determination engine 106.Effect of content acceptability determination engine 106 may receive adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. Any of virtual machines 11, 12 and/or 13 may examine the data inreal time as it loads onto the virtual machine 11, 12 and/or 13. Forinstance, if a link to a webpage immediately (e.g. as soon as the linkis activated) references an additional link (e.g. to redirect a user), avirtual machine 11, 12 and/or 13 may determine that such a reference toan additional link has been made. Virtual machines 11, 12 and/or 13 maydetermine whether data references additional data at any time when thedata is loading. Effect of content acceptability determination engine106 (FIG. 1A) may communicate an effect of content acceptabilitydetermination to a data provider engine 108 (FIG. 1A).

Operation 406 depicts determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences by issuing a request to a remote computerfor additional data information. Continuing the example above, FIG. 1Ashows the Effect of content acceptability determination engine 106.Effect of content acceptability determination engine 106 may receive adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B shows virtual machines 11, 12 and/or 13. The data of anadditional link or links may be examined by at least one of virtualmachines 11, 12 and/or 13 issuing a request to receive additional datainformation from a remote computer (e.g. a computer at a geographicallydistinct location).

Operation 408, illustrates determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences by examining a copy of data from alocation geographically distinct from a location of the data. Continuingthe example above, FIG. 1A shows the Effect of content acceptabilitydetermination engine 106. Effect of content acceptability determinationengine 106 may receive a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102 and communication of retrieved data to data content determinationengine 104. FIG. 1A further illustrates the Effect of contentacceptability determination engine 106 further including a virtualmachine module 118 and a user preference database 120. Virtual machinemodule 118 includes virtual machines 11, 12 and/or 13. Effect of contentacceptability determination engine 106 may transfer data received fromdata content determination engine 104 following a determination of datacontent. Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to thevirtual machine module 118. Virtual machine module 118 (FIG. 1A) mayspawn at least one virtual machine 11, 12, and/or 13 and transfer thedata and associated data content determination to at least one ofvirtual machines 11, 12 and/or 13. FIG. 1B shows virtual machines 11, 12and/or 13. The data of an additional link or links may be examined by atleast one of virtual machines 11, 12 and/or 13 issuing a request to aremote computer to examine additional data information at the remotecomputer (e.g. a computer at a geographically distinct location).

Further, operation 410 shows generating a substantial duplicate of atleast a part of a real machine at a location geographically distinctfrom a location of the data. Continuing the example above, FIG. 1A showsthe Effect of content acceptability determination engine 106. Effect ofcontent acceptability determination engine 106 may receive a datacontent determination from data content determination engine 104 postretrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. For instance, a virtual machine 11, 12 and/or 13 of the real machinemay be located at a geographically distinct location such as a remoteserver, or a remote system configured duplicate data from the realmachine 130 and to receive and examine real machine informationtransferred to the remote server or remote system. System 100 mayinclude any number of communication modules (not shown) configured tocommunicate over local or remote communication channels.

FIG. 5 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 5 illustrates example embodiments where theoperation 230 may include at least one additional operation. Additionaloperations may include an operation 502, an operation 504, an operation506, and/or an operation 508.

Operation 502, shows determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of a substantial portion of a real machine having one ormore end-user specified preferences. Continuing the example above, FIG.1A shows the Effect of content acceptability determination engine 106.Effect of content acceptability determination engine 106 may receive adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. For instance, FIG. 1B illustrates virtual machines 11, 12, 14including a virtual machine representation of content of the realmachine 130, software or the real machine 130, hardware of the realmachine 130, and an operating system of the real machine 130. Virtualmachines 11, 12 and/or 13 may include most or all of at least one of thecontent of the real machine 130 (e.g. a substantial portion of the text,image, audio, and video files of the real machine), software of the realmachine 130 (e.g. a substantial portion of any program or suite ofprograms installed on the real machine), hardware of the real machine130 (a substantial portion of the circuitry comprising the realmachine), and/or an operating system of the real machine 130 (e.g. asubstantial portion of a Windows® operating system installed on the realmachine).

Operation 504 depicts for determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a portion of data on a real machine havingone or more end-user specified preferences. Continuing the exampleabove, FIG. 1A shows the Effect of content acceptability determinationengine 106. Effect of content acceptability determination engine 106 mayreceive a data content determination from data content determinationengine 104 post retrieval of data by data retriever engine 102 andcommunication of retrieved data to data content determination engine104. FIG. 1A further illustrates the Effect of content acceptabilitydetermination engine 106 further including a virtual machine module 118and a user preference database 120. Virtual machine module 118 includesvirtual machines 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may transfer data received from data contentdetermination engine 104 following a determination of data content.Effect of content acceptability determination engine 106 may transferthe data and associated data content determination to the virtualmachine module 118. Virtual machine module 118 (FIG. 1A) may spawn atleast one virtual machine 11, 12, and/or 13 and transfer the data andassociated data content determination to at least one of virtualmachines 11, 12 and/or 13. FIG. 1B illustrates virtual machines 11, 12and/or 13 including a virtual machine representation of content of thereal machine 130, a virtual machine representation of software of thereal machine 130, a virtual machine representation of hardware of thereal machine 130, and/or a virtual machine representation of anoperating system of the real machine 130 post activation of link 1, link2, and link 3 of data 110 (e.g., a Web page) resident on real machine130. These post activation states are examples of effects of the contentof data 110. As additional examples, virtual machines 11, 12 and/or 13may include at least a portion of at least one of the content of thereal machine 130 (e.g. the video files of a real machine), software orthe real machine 130 (e.g. iTunes), hardware of the real machine 130(e.g. a data processor), and/or an operating system of the real machine130 (e.g. a portion of Netware®).

Operation 506, illustrates determining an acceptability of an effect ofdata at least in part via a virtual machine representation operating ata location of the data. Continuing the example above, FIG. 1A shows theEffect of content acceptability determination engine 106. Effect ofcontent acceptability determination engine 106 may receive a datacontent determination from data content determination engine 104 postretrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIGS. 1B further illustrates virtual machines 11, 12 and/or 13. Inone implementation, any of virtual machines 11, 12 and/or 13 may begenerated on the real machine 130 (e.g. as a subsystem of real machine130).

Operation 508, shows determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation operating at a location geographically distinct from alocation of the data. Continuing the example above, FIG. 1A shows theEffect of content acceptability determination engine 106. Effect ofcontent acceptability determination engine 106 may receive a datacontent determination from data content determination engine 104 postretrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 includes virtual machines 11,12 and/or 13. Effect of content acceptability determination engine 106may transfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B further illustrates virtual machines 11, 12 and/or 13. Inone implementation, any of virtual machines 11, 12 and/or 13 may begenerated on a remote server, remote operating system or otherwisegeographically distinct location with respect to the real machine 130.

FIG. 6 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 6 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 602, an operation 604, an operation 606, and/or anoperation 608.

Operation 602 depicts determining an acceptability of an effect of thecontent of the data on at least two virtual machine representations ofat least a part of a real machine having one or more end-user specifiedpreferences. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102 and communication of retrieved datato data content determination engine 104. FIG. 1A further illustratesthe Effect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B illustrates virtual machines 11, 12, and 13. At least two ofvirtual machines 11, 12 and/or 13 may include virtual machinerepresentations of at least a portion of software, hardware and anoperating system of the real machine 130.

Further, operation 604, illustrates determining an acceptability of aneffect of the content of the data on at least two virtual machinerepresentations of at least a part of a real machine having one or moreend-user specified preferences at least one of the at least two virtualmachine representations operating on a separate operating system.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106. Effect of content acceptabilitydetermination engine 106 may receive a data content determination fromdata content determination engine 104 post retrieval of data by dataretriever engine 102 and communication of retrieved data to data contentdetermination engine 104. FIG. 1A further illustrates the Effect ofcontent acceptability determination engine 106 further including avirtual machine module 118 and a user preference database 120. Virtualmachine module 118 includes virtual machines 11, 12 and/or 13. Effect ofcontent acceptability determination engine 106 may transfer datareceived from data content determination engine 104 following adetermination of data content. Effect of content acceptabilitydetermination engine 106 may transfer the data and associated datacontent determination to the virtual machine module 118. Virtual machinemodule 118 (FIG. 1A) may spawn at least one virtual machine 11, 12,and/or 13 and transfer the data and associated data contentdetermination to at least one of virtual machines 11, 12 and/or 13. Forinstance, a virtual machine 11, 12 and/or 13 (FIG. IA) may individuallymimic one of Windows XP, Windows 2000 with SQL 2000 and SharePointServer 2003, Windows 2003 with Exchange 2003, an Apple operating system(e.g., MAC OS 9, OS X Leopard), or Red Hat Linux with Apache. Further,each virtual machine 11, 12 and/or 13 may mimic a different operatingsystem (e.g., virtual machine 11 may mimic Windows XP, virtual machine12 may mimic Windows 2000 and virtual machine 13 may mimic Red Hat Linuxand so on). Operating system may be any software configured to managethe sharing of the resources of a computer, process system data and userinputs, and respond to user inputs by allocating and managing tasks andinternal system resources. Operating system may be, for exampleMicrosoft Windows® 2000, XP, or Vista available from MicrosoftCorporation of Redmond, Washington, Mac OS X, Linux or any otheroperating system.

Operation 606, shows determining an acceptability of an effect of thecontent of the data on at least two virtual machine representations ofat least a part of a real machine having one or more end-user specifiedpreferences, at least one of the at least two virtual machinerepresentations operating on a separate core of a system comprising atleast two cores. Continuing the example above, FIG. 1A shows the Effectof content acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102 and communication of retrieved datato data content determination engine 104. FIG. 1A further illustratesthe Effect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. As illustrated in FIGS. 1B and 1C, each of virtual machine 11,virtual machine 12, virtual machine 13, virtual machine 21, virtualmachine 22, and virtual machine 23 may operate on an individual core 11,12 and/or 13, 31, 32, 33, respectively, of a multi-core processor, orvirtual machine 11 may run on one core and virtual machines 12 and/or 13may run on the other core of a dual core processor such as an Intel®dual core processor and so on. The multi-core processor may include aplurality of processor cores packaged in one processor package. The termcore as used herein may refer, for example, to a single processor of amultiprocessor system, or to a processor core of a multi-core processor.Multi-core processor may be utilized as portable computers such aslaptop computers, personal digital assistants, or desktop computers, orservers, or another form of processor based system. Combinations ofthese types of platforms may be present. The multi-core system mayinclude a multi-core processor, each core comprising a separate addressspace, and having internal to that address space.

Operation 608, depicts determining an acceptability of an effect of thecontent of the data on at least two virtual machine representations ofat least a part of a real machine having one or more end-user specifiedpreferences, at least one of the at least two virtual machinerepresentations operating on a separate operating system at a locationof the data. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102 and communication of retrieved datato data content determination engine 104. FIG. 1A further illustratesthe Effect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. Each of virtual machines 11, 12 and/or 13 may operate on a separateoperating system at a location of the data (e.g. executed on asubsystem, such as the virtual machine module 118 (FIG. A) including aplurality of virtual machines 11, 12 and/or 13 (FIG. 1B) within the realmachine 130).

FIG. 7 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 7 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 702, an operation 704, an operation 706, and/or anoperation 708.

Operation 702, illustrates determining a state change of a virtualmachine representation between a prior state and a subsequent state ofthe virtual machine representation after loading at least a portion ofdata. Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer the data and associateddata content determination to at least one of virtual machines 11, 12and/or 13. A state change (e.g. a decrease in memory) of virtual machine11, 12 and/or 13 (FIG. 1B) may be determined by a component of virtualmachine 11, 12 and/or 13 measuring a characteristic of the virtualmachine representation of the content, software, hardware or operatingsystem of the real machine 130 before and after the at least a portionof data has loaded. For instance, a state change may be measured after asearch result containing a plurality of web links has loaded and atleast one web link has been activated.

Operation 704, shows determining a state of a virtual machinerepresentation prior to loading at least a portion of data. Continuingthe example above, FIG. 1A shows the Effect of content acceptabilitydetermination engine 106 including a virtual machine module 118 furtherincluding virtual machines 11, 12 and/or 13. Upon receiving data and adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102, Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to virtual machine module 118.Virtual machine module 118 may spawn at least one virtual machine 11,12, and/or 13 and transfer the data and associated data contentdetermination to at least one of virtual machines 11, 12 and/or 13.Virtual machine 11, 12 and/or 13 may determine a state of at least onecomponent (e.g. the hardware) of the virtual machine prior to activation(e.g. before) of a link. Virtual machine state may be representative ofa state for all or at least a portion of the components (e.g. content,software, hardware, operating system) of the real machine 130represented by the virtual machine 11, 12 and/or 13. For instance, avirtual machine 11, 12 and/or 13 may be determined to be free ofviruses, an amount of virtual machine memory may be measured, or aprocessing speed of the virtual machine 11, 12 and/or 13 may bedetermined. Virtual machines 11, 12 and/or 13 may contain a diagnosticapplication configured to analyze virtual machine performance andcontents.

Further, operation 706 depicts determining a state of a virtual machineafter loading at least a portion of data. Continuing the example above,FIG. 1A shows the Effect of content acceptability determination engine106 including a virtual machine module 118 further including virtualmachines 11, 12 and/or 13. Upon receiving data and a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102, Effect of content acceptabilitydetermination engine 106 may transfer the data and associated datacontent determination to virtual machine module 118. Virtual machinemodule 118 may spawn at least one virtual machine 11, 12, and/or 13 andtransfer the data and associated data content determination to at leastone of virtual machines 11, 12 and/or 13. Virtual machine 11, 12 and/or13 may determine a state of at least one component (e.g. the hardware)of the virtual machine subsequent to (e.g. after) activation of a link.For instance a virtual machine state may be representative of a statefor all characteristics of the real machine 130 content, software,hardware or operating system represented by the virtual machine 11, 12and/or 13 after at least a portion of the data has loaded. For instance,a virtual machine 11, 12 and/or 13 may be determined to contain a virus,an amount of virtual machine memory may be measured, or a processingspeed of the virtual machine 11, 12 and/or 13 may be determined. Virtualmachine 11, 12 and/or 13 may be examined to determine, for example, if avirus or any other undesired software is present on the machine after atleast a portion of the data has loaded by examining the virtual machinerepresentation of the operating system of the real machine 130 (FIG.1B), or if information from the real machine 130 has been transferred toan external location by examining the software of the real machine 130.

Operation 708 depicts determining whether the state change is anundesirable state change based on one or more end-user specifiedpreferences. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer the data and associateddata content determination to at least one of virtual machines 11, 12and/or 13. An undesirable state change may be determined by examiningthe changes to the virtual machine 11, 12 and/or 13 and comparing thestate change of the virtual machine 11, 12 and/or 13 to user preferencedatabase information spawned on virtual machines 11, 12 and/or 13 by atransfer of user preference database information from the userpreference database 120 (FIG. 1A) to the virtual machine module 118(FIG. 1A) which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. A state change may include any undesirable state changes such as adecrease in memory or processing speed and/or the presence of a virus orother undesirable software after at least a portion of the data hasloaded. Undesirable state changes may further include an undesirabletransfer of information located on the virtual machine 11, 12 and/or 13to an external location, an undesirable transfer of data onto thevirtual machine 11, 12 and/or 13 from an external location after atleast a portion of the data has loaded on the virtual machine 11, 12and/or 13 that may result in an undesired change in the state ofcontent, software, hardware or an operating system of the real machine130 and/or an undesirable transfer of data onto the virtual machine 11,12 and/or 13 where at least a portion of the transferred data may befound objectionable when viewed by a user 10.

FIG. 8 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 8 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 802, an operation 804, an operation 806, anoperation 808, and/or an operation 810.

Operation 802, illustrates determining an acceptability of an effect ofthe content of the data in response to at least one user setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. An undesirable state change may be determined by examining thechanges to the virtual machine 11, 12 and/or 13 and comparing the statechange of the virtual machine 11, 12 and/or 13 to user preferencedatabase information spawned on virtual machines 11, 12 and/or 13 by atransfer of user preference database information from the userpreference database 120 (FIG. 1A) to the virtual machine module 118(FIG. 1A) which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. User preference database 120 may include at least one end-userspecified preference relating to at least one of content, software,hardware and/or an operating system of a real machine 130. At least oneof virtual machines 11, 12 and/or 13 may determine an acceptability ofan effect of the content of the data based on at least one user settingcontained in a user preference database at least a portion of which maybe spawned onto virtual machines 11, 12 and/or 13 via virtual machinemodule 118 (e.g., does a website contain only images, text, audio orvisual data suitable for viewing by a user based on a settingestablished by a user such as a political or cultural preferencesetting). Further examples of user preferences include specific religionor lifestyle preference, such as “return only links relating to RomanCatholicism” or “return only links relating to a vegan lifestyle” thatmay be stored in the real machine 130. User-specific preference may alsorelate to user information safety or computer safety, such as “do notdisplay links requesting information from my computer,” or “do notdisplay links that transfer viruses onto my computer.”

Operation 804, shows determining an acceptability of an effect of thecontent of the data in response to a personal user setting. Continuingthe example above, FIG. 1A shows the Effect of content acceptabilitydetermination engine 106 including a virtual machine module 118 furtherincluding virtual machines 11, 12 and/or 13. Upon receiving data and adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102, Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to virtual machine module 118.Virtual machine module 118 may spawn at least one virtual machine 11,12, and/or 13 and transfer data and associated data contentdetermination to at least one of virtual machines 11, 12 and/or 13. Userpreference database information stored in the user preference database120 (FIG. 1A) may be transferred to the virtual machine module 118 (FIG.1A), which spawns a copy of at least a portion of the user preferencedatabase 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13. Virtualmachines 11, 12 and/or 13 may compare the data received from the virtualmachine module to a personal user setting (e.g. “show only automobilerelated data”) contained in user preference database information spawnedon virtual machines 11, 12 and/or 13. User preference database 120 mayinclude at least one personal user setting relating to at least one ofcontent, software, hardware and/or an operating system of a real machine130. Personal user setting may be a setting input by a user that ispersonal to the user, such as an information security level, a contentfilter level, or a personal desirability setting such as “show onlynon-religious data” or “show only automobile related data.”

Further, operation 806 depicts determining an acceptability of an effectof the content of the data in response to a peer user setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module to a peer user setting contained in userpreference database information spawned on virtual machines 11, 12and/or 13. User preference database 120 may include at least one peeruser setting relating to at least one of content, software, hardwareand/or an operating system of a real machine 130. Peer user setting maybe a setting input by a user that is determined by a peer group, such asa peer group determined information security level such as “display only100 percent secure websites”, a peer group determined data filter levelsuch as “filter 100% of obscene data”, or a peer group desirabilitysetting such as “show only classical music related data” or “show onlyknitting related data.”

Additionally, operation 808, illustrates determining an acceptability ofan effect of the content of the data in response to a corporate usersetting. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer,data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a corporate user setting contained inuser preference database information spawned on virtual machines 11, 12and/or 13. User preference database 120 may include at least onecorporate user setting relating to at least one of content, software,hardware and/or an operating system of a real machine 130. Corporateuser setting may be a setting inp.ut by a corporation that is determinedto the corporation, such as a corporate desirability setting such as“show only real-estate related data” or “show only agricultural relateddata.”

Further, operation 810, shows determining an acceptability of an effectof the content of the data in response to a work safety user setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a work safety user setting containedin user preference database information spawned on virtual machines 11,12 and/or 13. User preference database 120 may include at least one worksafety user setting relating to at least one of content, software,hardware and/or an operating system of a real machine 130. Thus, in onespecific example, a webpage or website data may be determined to bedetermined to be displayable if the data satisfies a work safety usersetting such as a corporate information security level, corporate usersetting, or a corporate information content filter level corporate usersetting.

FIG. 9 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 9 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 902, an operation 904, an operation 906, anoperation 908, an operation 910, and/or an operation 912.

Operation 902 depicts determining an acceptability of an effect of thecontent of the data in response to a desirability setting. Continuingthe example above, FIG. 1A shows the Effect of content acceptabilitydetermination engine 106 including a virtual machine module 118 furtherincluding virtual machines 11, 12 and/or 13. Upon receiving data and adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102, Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to virtual machine module 118.Virtual machine module 118 may spawn at least one virtual machine 11,12, and/or 13 and transfer data and associated data contentdetermination to at least one of virtual machines 11, 12 and/or 13. Userpreference database information stored in the user preference database120 (FIG. 1A) may be transferred to the virtual machine module 118 (FIG.1A), which spawns a copy of at least a portion of the user preferencedatabase 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13. Virtualmachines 11, 12 and/or 13 may compare the data received from the virtualmachine module 118 to a desirability setting (e.g., does a websitecontain only images, text, audio or visual data suitable for viewing bya user based on a desirability setting established by a user such as adesire to view only non-obscene material) contained in user preferencedatabase information spawned on virtual machines 11, 12 and/or 13. Userpreference database 120 may include at least one desirability settingrelating to at least one of content, software, hardware and/or anoperating system of a real machine 130.

Operation 904, illustrates determining an acceptability of an effect ofthe content of the data in response to a religious desirability setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a religious desirability setting(e.g., does a website contain only images, text, audio or visual datasuitable for viewing by a user based on a religious desirability settingestablished by a user such as a desire to view only Hindu material)contained in user preference database information spawned on virtualmachines 11, 12 and/or 13. A religious desirability setting may beinclude any setting regarding a major, minor, or other religion such asChristianity, Judaism, Islam, Hinduism, and so on.

Operation 906, shows determining an acceptability of an effect of thecontent of the data in response to a political desirability setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a political desirability setting(e.g., does a website contain only images, text, audio or visual datasuitable for viewing by a user based on a political desirability settingestablished by a user such as a desire to view only Democratic Partymaterial) contained in user preference database information spawned onvirtual machines 11, 12 and/or 13. A political desirability setting mayinclude any setting regarding a political party or affiliation (e.g.Republican, Democratic, Libertarian, Green Party, etc.).

Operation 908 depicts determining an acceptability of an effect of thecontent of the data in response to a cultural desirability setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a cultural desirability setting (e.g.,does a website contain only images, text, audio or visual data suitablefor viewing by a user based on a cultural desirability settingestablished by a user such as a desire to view only materials regardingearly Mayan civilization) contained in user preference databaseinformation spawned on virtual machines 11, 12 and/or 13. A culturaldesirability setting may include any culturally related information suchas a religious, ethnic, regional, or heritage based culturaldesirability setting or any other cultural desirability setting.

Operation 910, illustrates determining an acceptability of an effect ofthe content of the data in response to a theme related desirabilitysetting. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a theme related desirability setting(e.g., does a website contain only images, text, audio or visual datasuitable for viewing by a user based on a theme related desirabilitysetting established by a user such as a desire to view only materialsregarding collectible stamps) contained in user preference databaseinformation spawned on virtual machines 11, 12 and/or 13. A themerelated desirability setting may include any theme related information,such as information relating to cars, fashion, electronics, sports,hobbies, collector's items, or any theme or category that may be ofinterest to a user.

Operation 912, shows determining an acceptability of an effect of thecontent of the data in response to an age appropriateness desirabilitysetting. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to an age appropriateness desirabilitysetting (e.g., does a website contain only images, text, audio or visualdata suitable for viewing by a user based on an age appropriatenessdesirability setting established by a user such as a desire to view onlymaterials given a PG or lower rating as determined by the Motion Pictureof America Association film rating system) contained in user preferencedatabase information spawned on virtual machines 11, 12 and/or 13. Anage appropriateness desirability setting may include any age appropriatesetting, such as a rating threshold or a profanity threshold.

FIG. 10 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 10 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 1002, an operation 1004, an operation 1006, and/oran operation 1008.

Operation 1002 depicts determining an acceptability of an effect of thecontent of the data in response to at least one privacy related setting.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a privacy related setting (e.g., doesa website contain only images, text, audio or visual data suitable forviewing by a user based on a privacy related setting established by auser) contained in user preference database information spawned onvirtual machines 11, 12 and/or 13. A privacy related setting may includeany privacy related settings (e.g., does a website contain only datathat will not request information from my computer or allow others toview personal information saved on my computer).

Operation 1004, illustrates determining an acceptability of an effect ofthe content of the data in response to a user specific privacy relatedsetting. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a user specific privacy relatedsetting (e.g., will a website request specific information about theuser such as name, address, telephone number) contained in userpreference database information spawned on virtual machines 11, 12and/or 13. A user specific privacy related setting may include any userspecific privacy related settings (e.g., a setting relating to a user'sbiographical information or financial information).

Further, operation 1006, shows determining an acceptability of an effectof the content of the data in response to a group privacy relatedsetting. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a group privacy related setting (e.g.,will a website request information about an organization such as name,address, telephone number) contained in user preference databaseinformation spawned on virtual machines 11, 12 and/or 13. A groupprivacy related setting may include any group privacy related settings(e.g., a setting relating to a group's membership). Group privacyrelated setting may be any setting established by a group such as a workgroup (e.g. employees of a company), a peer group (e.g., members of abook club), or a family group (e.g. members of family unit) privacyrelated setting.

Further, operation 1008 depicts determining an acceptability of aneffect of the content of the data in response to a corporate privacyrelated setting. Continuing the example above, FIG. 1A shows the Effectof content acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to a corporate privacy related setting(e.g., will a website request information about a corporation such asdata stored on a real machine belonging to the corporation) contained inuser preference database information spawned on virtual machines 11, 12and/or 13. Corporate privacy related setting may be determined by acorporate issued privacy manual, or other such document or mandate setforth by officers of a corporation.

FIG. 11 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 11 illustrates example embodiments where thedetermining an acceptability of the effect of the data operation 230 mayinclude at least one additional operation. Additional operations mayinclude an operation 1102, an operation 1104, an operation 1106, and/oran operation 1108.

Operation 1102, illustrates determining an acceptability of an effect ofthe content of the data in response to a type of transmitted userinformation. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to at least one acceptable type oftransmitted user information setting (e.g., do not return links thatwill transmit my e-mail address, home address or telephone number to anexternal location) contained in user preference database informationspawned on virtual machines 11, 12 and/or 13. Acceptable type oftransmitted user information setting may be determined by a user 10(FIG. 1B). For instance, acceptability of the effect of the data may bedetermined in response to whether or not private user information, suchas credit card numbers, bank accounts, personal identificationinformation or any other personal user information may be transmitted toa location external to the real machine by selecting the link.

Further, operation 1104, shows determining an acceptability of an effectof the content of the data in response to a type of captured userinformation. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to at least one acceptable type ofcaptured user information setting (e.g., do not return links that willcapture my e-mail address, home address or telephone number) containedin user preference database information spawned on virtual machines 11,12 and/or 13. Acceptable type of captured user information setting maybe determined by a user 10 (FIG. 1B). For instance, acceptability of theeffect of the data may be determined in response to whether or notprivate user information, such as credit card numbers, bank accounts,personal identification information or any other personal userinformation may be captured by a machine located at a location externalto the real machine by selecting the link.

Further, operation 1106, illustrates determining an acceptability of aneffect of the content of the data in response to a type of exposed userinformation. Continuing the example above, FIG. 1A shows the Effect ofcontent-acceptability determination engine 106 including a virtualmachine module 118 further including virtual machines 11, 12 and/or 13.Upon receiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. User preference database information stored in the user preferencedatabase 120 (FIG. 1A) may be transferred to the virtual machine module118 (FIG. 1A), which spawns a copy of at least a portion of the userpreference database 120 (FIG. 1A) onto virtual machines 11, 12 and/or13. Virtual machines 11, 12 and/or 13 may compare the data received fromthe virtual machine module 118 to at least one acceptable type ofexposed user information setting (e.g., do not return links that willexpose personal financial information stored on the real machine 130)contained in user preference database information spawned on virtualmachines 11, 12 and/or 13. Acceptable type of exposed user informationsetting may be determined by a user 10 (FIG. 1B). For instance,acceptability of the effect of the data may be determined in response towhether or not private user information, such as credit card numbers,bank accounts, personal identification information or any other personaluser information may be exposed to a machine located at a locationexternal to the real machine by selecting the link.

Operation 1108, shows determining an acceptability of an effect of thecontent of the data in response to visually examining a data image.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106 including a virtual machinemodule 118 further including virtual machines 11, 12 and/or 13. Uponreceiving data and a data content determination from data contentdetermination engine 104 post retrieval of data by data retriever engine102, Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to virtualmachine module 118. Virtual machine module 118 may spawn at least onevirtual machine 11, 12, and/or 13 and transfer data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. To visually examine a data image, a virtual machine 11, 12 and/or 13may include an image scanning module. Visually examining the data imagemay include, for example, color analysis, pattern-matching,pattern-recognition, or any other technique for recognizing a particularimage or type of image.

FIG. 12 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 12 illustrates example embodiments where thedetermining an acceptability of the effect of the data of the dataoperation 230 may include at least one additional operation. Additionaloperations may include an operation 1202.

Operation 1202, depicts determining an acceptability of an effect of thecontent of the data on at least two virtual machine representations ofat least a part of a real machine having one or more end-user specifiedpreferences, at least one of the at least two virtual machinerepresentations operating on a separate operating system at a locationgeographically distinct from a location of the data. Continuing theexample above, FIG. 1A shows the Effect of content acceptabilitydetermination engine 106 including a virtual machine module 118 furtherincluding virtual machines 11, 12 and/or 13. Upon receiving data and adata content determination from data content determination engine 104post retrieval of data by data retriever engine 102, Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to virtual machine module 118.Virtual machine module 118 may spawn at least one virtual machine 11,12, and/or 13 and transfer data and associated data contentdetermination to at least one of virtual machines 11, 12 and/or 13. Userpreference database information stored in the user preference database120 (FIG. 1A) may be transferred to the virtual machine module 118 (FIG.1A), which spawns a copy of at least a portion of the user preferencedatabase 120 (FIG. 1A) onto virtual machines 11, 12 and/or 13. At leasttwo virtual machines, for example virtual machines 12 and/or 13 may bevirtual machines operating at geographically distinct location such as aremote server, or a remote system configured to receive and examine realmachine information transferred to the remote system and duplicate datafrom the real machine 130. In some instances, each virtual machine maybe generated on one or more separate cores of a multi-core processor.

FIG. 13 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 13 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1302, an operation 1304, an operation 1306, an operation 1308,and/or an operation 1310.

Operation 1302 illustrates providing a data display option of displayingthe data. Continuing the example above, data provider engine 108 (FIG.1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. IA), which may receive data and anassociated data content determination (e.g. data is a video file) fromdata content determination engine 104 (FIG. 1A) post retrieval of databy data retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of displaying at least a portion of the data. Forinstance, data content provider engine 108 may receive at least onedisplay instruction (e.g. OK to display the entire text of link 1) fromat least one component of Effect of content acceptability determinationengine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 mayinclude one or more instruction generating modules configured to providean instruction to the Effect of content acceptability determinationengine 106 after a comparison of an activation of a link to a userpreference stored in a copy of the user preference database 120 (FIG.1A) spawned on the virtual machine 11, 12 and/or 13. Effect of contentacceptability determination engine 106 may communicate the displayinstruction to the data content provider engine 108. Data contentprovider engine 108 may then display the data. Displayed data may be anunmodified web page of text, images and/or video, or a web pageincluding links to additional web pages and may be displayed on a realmachine display such as a computer screen.

Operation 1304, shows providing a data display option of not displayingthe data. Continuing the example above, data provider engine 108 (FIG.1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination (e.g. data is a video file) fromdata content determination engine 104 (FIG. 1A) post retrieval of databy data retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of not displaying at least a portion of the data. Forinstance, data content provider engine 108 may receive at least one donot display instruction (e.g. Do not display the text of link 1) from atleast one component of Effect of content acceptability determinationengine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 mayinclude one or more instruction generating modules configured to providea do not display instruction to the Effect of content acceptabilitydetermination engine 106 after a comparison of an activation of a linkto a user preference stored in a copy of the user preference database120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect ofcontent acceptability determination engine 106 may communicate the donot display instruction to the data content provider engine 108. Thedata display option of not displaying the data may include a messageindicated why the data is not being displayed, or may be, for example, ablank page displayed on a display of the real machine.

Operation 1306 depicts providing a data display option of displaying amodified version of the data. Continuing the example above, dataprovider engine 108 (FIG. 1A) may be in communication with Effect ofcontent acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination (e.g. data isa video file) from data content determination engine 104 (FIG. 1A) postretrieval of data by data retriever engine 102 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may transfer effect ofcontent acceptability determination to the data provider engine 108 toprovide the data display option of displaying at least a portion of thedata. For instance, data content provider engine 108 may receive atleast one modify data instruction (e.g. display only lines 1-10 of thetext of link 1) from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide a modify data instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a user preference stored in a copy of the userpreference database 120 (FIG. 1A) spawned on the virtual machine 11, 12and/or 13. Effect of content acceptability determination engine 106 maycommunicate the modify data instruction to the data content providerengine 108. The data content provider engine 108 may transmit the modifydata instruction to the data modification engine 122 for modification ofthe data. Data modification engine may transmit the modified data to thedata content provider engine 108. Data content provider engine 108 maythen display the modified version of the data. Displayed data may be amodified web page of text, a modified image and/or a modified video, ora modified web page including links to additional web pages. Forinstance, a webpage or website may be displaying, but any obscenities onthe web page or website may replaced by non-obscene word alternatives.

Further, operation 1308, illustrates providing a data display option ofobfuscating an objectionable data portion. Continuing the example above,data provider engine 108 (FIG. 1A) may be in communication with Effectof content acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination (e.g. data isa video file) from data content determination engine 104 (FIG. 1A) postretrieval of data by data retriever engine 102 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may transfer effect ofcontent acceptability determination to the data provider engine 108 toprovide the data display option of obfuscating (e.g. blurring) a portionof the data (e.g. obscene photos). For instance, data content providerengine 108 may receive at least one obfuscate data instruction (e.g.display only non-obscene portions of the image in link 1) from at leastone component of Effect of content acceptability determination engine106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may include oneor more instruction generating modules configured to provide anobfuscate data instruction to the Effect of content acceptabilitydetermination engine 106 after a comparison of an activation of a linkto a user preference stored in a copy of the user preference database120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect ofcontent acceptability determination engine 106 may communicate theobfuscate data instruction to the data content provider engine 108. Thedata content provider engine 108 may transmit the obfuscate datainstruction to the data modification engine 122 which may transmit theobfuscate data instruction to the data obfuscation engine 124. Dataobfuscation engine 124 may transmit the obfuscated data to the datamodification engine 122 for transmission to the data content providerengine 108. Data content provider engine 108 may then display theobfuscated version of the data. For example, obfuscating logic mayobfuscate restricted data or imagery within a webpage or image.Obfuscation may include blurring or blocking of the objectionable dataportion.

Further, operation 1310, shows providing a data display option ofanonymizing an objectionable data portion. Continuing the example above,data provider engine 108 (FIG. 1A) may be in communication with Effectof content acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination (e.g. data isa video file) from data content determination engine 104 (FIG. 1A) postretrieval of data by data retriever engine 102 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may transfer effect ofcontent acceptability determination to the data provider engine 108 toprovide the data display option of anonymizing (e.g. obscuring sourceinformation) for a portion of the data (e.g. graphic videos). Forinstance, data content provider engine 108 may receive at least oneanonymize data instruction (e.g. obscure source information for portionsof the video in link 1) from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide an anonymize data instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a user preference stored in acopy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the anonymize data instructionto the data content provider engine 108. The data content providerengine 108 may transmit the anonymize data instruction to the datamodification engine 122 which may transmit the anonymize datainstruction to the data anonymization engine 126. Data anonymizationengine 126 may transmit the anonymized data to the data modificationengine 122 for transmission to the data content provider engine 108.Data content provider engine 108 may then display the anonymized versionof the data. Anonymized data may be data in which the original identityinformation of the data is hidden, obscured, replaced, and/or otherwisemodified.

FIG. 14 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 14 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1402, an operation 1404, an operation 1406, and/or anoperation 1408.

Operation 1402, shows providing a data display option of removing,altering, or replacing an objectionable data portion. Continuing theexample above, data provider engine 108 (FIG. 1A) may be incommunication with Effect of content acceptability determination engine106 (FIG. 1A), which may receive data and an associated data contentdetermination (e.g. data is an audio file) from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of removing, altering or replacing an objectionable dataportion (e.g. replacing profanity with innocuous language) for a portionof the data (e.g. explicit lyrics). For instance, data content providerengine 108 may receive at least one alter, remove or replace instruction(e.g. obscure source information for portions of the video in link 1)from at least one component of Effect of content acceptabilitydetermination engine 106 (FIG. 1A). Each of virtual machines 11, 12and/or 13 may include one or more instruction generating modulesconfigured to provide a remove, alter or replace data instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a user preference stored in acopy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the remove, alter or replacedata instruction to the data content provider engine 108. The datacontent provider engine 108 may transmit the anonymize data instructionto the data modification engine 122 which may then remove, alter orreplace the data. Data modification engine 122 may transmit the datacontaining removed, altered or replaced portions to the data contentprovider engine 108. Data content provider engine 108 may then displaythe data containing removed, altered, or replaced portions. Thus, in onespecific example, a portion of a webpage produced by a search includingdata relating to religions other than Catholicism may be removed fromthe web page prior to display of the data on a real machine display suchas a computer screen.

Operation 1404 depicts providing a data display option of displaying adata portion consistent with at least one setting. Continuing theexample above, data provider engine 108 (FIG. 1A) may be incommunication with Effect of content acceptability determination engine106 (FIG. 1A), which may receive data and an associated data contentdetermination (e.g. data is text) from data content determination engine104 (FIG. 1A) post retrieval of data by data retriever engine 102 (FIG.1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of displayingdata consistent with at least one setting. For instance, data contentprovider engine 108 may receive at least one display instruction (e.g.OK to display only text consistent with a corporate established setting)from at least one component of Effect of content acceptabilitydetermination engine 106 (FIG. 1A). Each of virtual machines 11, 12and/or 13 may include one or more instruction generating modulesconfigured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a user setting stored in a copy of the userpreference database 120 (FIG. 1A) spawned on the virtual machine 11, 12and/or 13. Effect of content acceptability determination engine 106 maycommunicate the display instruction to the data content provider engine108. If data needs to be modified to be consistent with at least onesetting, the data content provider engine 108 may transmit the modifydata instruction to the data modification engine 122 for modification ofthe data. Data modification engine 122 may transmit the modified data tothe data content provider engine 108 (e.g., a setting such as recast alltext to large, and reformat a page consistent with the large text, suchas might be done for an individual having special vision needs). Datacontent provider engine 108 may then display the data consistent withthe setting.

Further, operation 1406, illustrates providing a data display option ofdisplaying a data portion consistent with a privacy related setting.Continuing the example above, data provider engine 108 (FIG. 1A) may bein communication with Effect of content acceptability determinationengine 106 (FIG. 1A), which may receive data and an associated datacontent determination (e.g. data does not contain spyware) from datacontent determination engine 104 (FIG. 1A) post retrieval of data bydata retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of displaying data consistent with at least one privacyrelated setting. For instance, data content provider engine 108 mayreceive at least one display instruction (e.g. OK to display webpage)from at least one component of Effect of content acceptabilitydetermination engine 106 (FIG. 1A). Each of virtual machines 11, 12and/or 13 may include one or more instruction generating modulesconfigured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a privacy related setting stored in a copy ofthe user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the display instruction to the data contentprovider engine 108. If data needs to be modified to be consistent withat least one privacy related setting, the data content provider engine108 may transmit the modify data instruction to the data modificationengine 122 for modification of the data. Data modification engine 122may transmit the modified data to the data content provider engine 108.Data content provider engine 108 may then display the data consistentwith the privacy related setting. For instance, a portion of a returnedwebpage including data requesting private user information such as auser's social security number or e-mail address may be removed from theweb page prior to display of the data on a computer screen. Furtherspecific examples include a webpage or website data may be determined tobe displayable if the data satisfies a setting such as a privacy relatedsetting such as a setting relating to a user's biographical informationor financial information, a webpage or website data may be determined tobe displayable if the data satisfies a group privacy related settingsuch as a work group (e.g. employees of a company), a peer group (e.g.,members of a book club), or a family group (e.g. members of family unit)privacy related setting, or a webpage or website data may be determinedto be displayable if the data satisfies a privacy setting determined bya corporation or other organization to maintain corporate ororganization privacy.

Further, operation 1408, shows providing a data display option ofdisplaying a data portion consistent with a user setting. Continuing theexample above, data provider engine 108 (FIG. 1A) may be incommunication with Effect of content acceptability determination engine106 (FIG. 1A), which may receive data and an associated data contentdetermination (e.g. data does not contain malware) from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of displaying data consistent with at least one usersetting. For instance, data content provider engine 108 may receive atleast one display instruction (e.g. OK to display webpage) from at leastone component of Effect of content acceptability determination engine106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may include oneor more instruction generating modules configured to provide aninstruction to the Effect of content acceptability determination engine106 after a comparison of an activation of a link to a user settingstored in a copy of the user preference database 120 (FIG. 1A) spawnedon the virtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the display instruction to thedata content provider engine 108. If data needs to be modified to beconsistent with at least one user setting, the data content providerengine 108 may transmit the modify data instruction to the datamodification engine 122 for modification of the data. Data modificationengine 122 may transmit the modified data to the data content providerengine 108. Data content provider engine 108 may then display the dataconsistent with the user setting. Thus, a webpage or website data may bedetermined to be displayable if the data satisfies a user setting whenthe virtual machine 11, 12 and/or 13 compares the data to the usersetting. For instance, a portion of a webpage produced by a searchincluding non-English text may be removed from the web page prior todisplay of the data on a computer screen. Further, in one specificexample, a webpage or website data may be determined to be displayableif the data satisfies a peer user setting, or a webpage or website datamay be determined to be displayable if the data satisfies, for instance,a corporate user setting.

FIG. 15 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 15 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1502, and/or an operation 1504.

Operation 1502 depicts providing a data display option of displaying adata portion consistent with a desirability setting. Continuing theexample above, data provider engine 108 (FIG. 1A) may be incommunication with Effect of content acceptability determination engine106 (FIG. 1A), which may receive data and an associated data contentdetermination (e.g. data is an image) from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of displayingdata consistent with at least one desirability setting. For instance,data content provider engine 108 may receive at least one displayinstruction (e.g. OK to display image) from at least one component ofEffect of content acceptability determination engine 106 (FIG. 1A). Eachof virtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide an instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a desirability setting stored in a copy of theuser preference database 120 (FIG. 1A) spawned on the virtual machine11, 12 and/or 13. Effect of content acceptability determination engine106 may communicate the display instruction to the data content providerengine 108. If data needs to be modified to be consistent with at leastone desirability setting, the data content provider engine 108 maytransmit the modify data instruction to the data modification engine 122for modification of the data. Data modification engine 122 may transmitthe modified data to the data content provider engine 108. Data contentprovider engine 108 may then display the data portion consistent withthe desirability setting. For instance, the data display option may bedisplaying on a display of a real machine only a data portion consistentwith a Christian desirability setting such as “display only Christianityrelated data.” In other examples, a webpage or website data may bedetermined to be displayable if the data satisfies a desirabilitysetting, a webpage or website data may be determined to be displayableif the data satisfies a religious desirability setting such as aChristian, Jewish, and/or Muslim, based religious desirability setting,or may be based on any other major, minor or alternative religiousdesirability setting, a webpage or website data may be determined to bedisplayable if the data satisfies a political desirability setting suchas a Republican, Democratic, Libertarian or Green Party politicaldesirability setting, a webpage or website data may be determined to bedisplayable if the data satisfies a cultural desirability setting suchas a religious, ethnic, regional, or heritage based culturaldesirability setting or any other cultural desirability setting, awebpage or website data may be determined to be displayable if the datasatisfies a theme related desirability setting such as boating or cardgames, or a webpage or website data may be determined to be displayableif the data satisfies an age appropriateness desirability setting suchas a setting based on the Motion Picture of America Association filmrating system.

Further, operation 1504, illustrates providing a data display option ofdisplaying a data portion consistent with a workplace establishedsetting. Continuing the example above, data provider engine 108 (FIG.1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination (e.g. data is a social networkingsite) from data content determination engine 104 (FIG. 1A) postretrieval of data by data retriever engine 102 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may transfer effect ofcontent acceptability determination to the data provider engine 108 toprovide the data display option of displaying data consistent with atleast one workplace established setting. For instance, data contentprovider engine 108 may receive at least one display instruction (e.g.do not display data) from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a workplace established setting stored in a copyof the user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the display instruction to the data contentprovider engine 108. If data needs to be modified to be consistent withat least one workplace established setting, the data content providerengine 108 may transmit the modify data instruction to the datamodification engine 122 for modification of the data. Data modificationengine 122 may transmit the modified data to the data content providerengine 108. Data content provider engine 108 may then display the dataportion consistent with the workplace established setting. For instance,the data display option may be displaying on a display of a real machineonly a data portion consistent with a workplace appropriatenessdesirability setting such as “display only non-obscene data.”

FIG. 16 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 16 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1602, an operation 1604, and/or an operation 1606.

Operation 1602, shows providing a data display option of displaying adata portion consistent with a safety setting. Continuing the exampleabove, data provider engine 108 (FIG. 1A) may be in communication withEffect of content acceptability determination engine 106 (FIG. 1A),which may receive data and an associated data content determination(e.g. data is an image) from data content determination engine 104 (FIG.1A) post retrieval of data by data retriever engine 102 (FIG. 1A).Effect of content acceptability determination engine 106 may transfereffect of content acceptability determination to the data providerengine 108 to provide the data display option of displaying dataconsistent with at least one safety setting. For instance, data contentprovider engine 108 may receive at least one display instruction (e.g.OK to display image) from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a safety setting stored in a copy of the userpreference database 120 (FIG. 1A) spawned on the virtual machine 11, 12and/or 13. Effect of content acceptability determination engine 106 maycommunicate the display instruction to the data content provider engine108. If data needs to be modified to be consistent with at least onesafety setting, the data content provider engine 108 may transmit themodify data instruction to the data modification engine 122 formodification of the data. Data modification engine 122 may transmit themodified data to the data content provider engine 108. Data contentprovider engine 108 may then display the data portion consistent withthe safety setting. For instance, the data display option may bedisplaying on a display of a real machine only a data portion consistentwith child safety setting such as “display only non-violent data,” or“display only ethnic and gender neutral data.”

Further, operation 1604 depicts providing a data display option ofdisplaying a data portion consistent with a public safety setting.Continuing the example above, data provider engine 108 (FIG. 1A) may bein communication with Effect of content acceptability determinationengine 106 (FIG. 1A), which may receive data and an associated datacontent determination (e.g. data is an image) from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of displaying data consistent with at least onedesirability setting. For instance, data content provider engine 108 mayreceive at least one display instruction (e.g. OK to display image) fromat least one component of Effect of content acceptability determinationengine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 mayinclude one or more instruction generating modules configured to providean instruction to the Effect of content acceptability determinationengine 106 after a comparison of an activation of a link to adesirability setting stored in a copy of the user preference database120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect ofcontent acceptability determination engine 106 may communicate thedisplay instruction to the data content provider engine 108. If dataneeds to be modified to be consistent with at least one public safetysetting, the data content provider engine 108 may transmit the modifydata instruction to the data modification engine 122 for modification ofthe data. Data content provider engine 108 may then display the dataportion consistent with the public safety setting. For instance, thedata display option may be displaying on a display of a real machineonly a data portion consistent with public safety setting such as“display only non-confidential data.”

Further, operation 1606, illustrates providing a data display option ofdisplaying a data portion consistent with a home safety setting.Continuing the example above, data provider engine 108 (FIG. 1A) may bein communication with Effect of content acceptability determinationengine 106 (FIG. 1A), which may receive data and an associated datacontent determination from data content determination engine 104 (FIG.1A) post retrieval of data by data retriever engine 102 (FIG. 1A).Effect of content acceptability determination engine 106 may transfereffect of content acceptability determination to the data providerengine 108 to provide the data display option of displaying dataconsistent with at least one home safety setting. For instance, datacontent provider engine 108 may receive at least one display instructionfrom at least one component of Effect of content acceptabilitydetermination engine 106 (FIG. 1A). Each of virtual machines 11, 12and/or 13 may include one or more instruction generating modulesconfigured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a home safety setting stored in a copy of theuser preference database 120 (FIG. 1A) spawned on the virtual machine11, 12 and/or 13. Effect of content acceptability determination engine106 may communicate the display instruction to the data content providerengine 108. If data needs to be modified to be consistent with at leastone home safety setting, the data content provider engine 108 maytransmit the modify data instruction to the data modification engine 122for modification of the data. Data content provider engine 108 may thendisplay the data portion consistent with the home safety setting. Forinstance, the data display option may be displaying on a display of areal machine only a data portion consistent with home safety settingsuch as “okay to display private or confidential data.”

FIG. 17 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 17 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1702, and/or an operation 1704.

Operation 1702 shows providing a data display option of displaying adata portion consistent with a workplace safety setting. Continuing theexample above, data provider engine 108 (FIG. 1A) may be incommunication with Effect of content acceptability determination engine106 (FIG. 1A), which may receive data and an associated data contentdetermination from data content determination engine 104 (FIG. 1A) postretrieval of data by data retriever engine 102 (FIG. 1A). Effect ofcontent acceptability determination engine 106 may transfer effect ofcontent acceptability determination to the data provider engine 108 toprovide the data display option of displaying data consistent with atleast one workplace safety setting. For instance, data content providerengine 108 may receive at least one display instruction from at leastone component of Effect of content acceptability determination engine106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 may include oneor more instruction generating modules configured to provide aninstruction to the Effect of content acceptability determination engine106 after a comparison of an activation of a link to a workplace safetysetting stored in a copy of the user preference database 120 (FIG. 1A)spawned on the virtual machine 11, 12 and/or 13. Effect of contentacceptability determination engine 106 may communicate the displayinstruction to the data content provider engine 108. If data needs to bemodified to be consistent with at least one workplace safety setting,the data content provider engine 108 may transmit the modify datainstruction to the data modification engine 122 for modification of thedata. Data content provider engine 108 may then display the data portionconsistent with the workplace safety setting. For instance, the datadisplay option may be displaying on a display of a real machine only adata portion consistent with a workplace safety setting such as “displayonly non-personal data.”

Further, operation 1704 shows providing a data display option ofdisplaying a data portion consistent with a child safety setting.Continuing the example above, data provider engine 108 (FIG. 1A) may bein communication with Effect of content acceptability determinationengine 106 (FIG. 1A), which may receive data and an associated datacontent determination from data content determination engine 104 (FIG.1A) post retrieval of data by data retriever engine 102 (FIG. 1A).Effect of content acceptability determination engine 106 may transfereffect of content acceptability determination to the data providerengine 108 to provide the data display option of displaying dataconsistent with at least one child safety setting. For instance, datacontent provider engine 108 may receive at least one display instructionfrom at least one component of Effect of content acceptabilitydetermination engine 106 (FIG. 1A). Each of virtual machines 11, 12and/or 13 may include one or more instruction generating modulesconfigured to provide an instruction to the Effect of contentacceptability determination engine 106 after a comparison of anactivation of a link to a child safety setting stored in a copy of theuser preference database 120 (FIG. 1A) spawned on the virtual machine11, 12 and/or 13. Effect of content acceptability determination engine106 may communicate the display instruction to the data content providerengine 108. If data needs to be modified to be consistent with at leastone child safety setting, the data content provider engine 108 maytransmit the modify data instruction to the data modification engine 122for modification of the data. Data content provider engine 108 may thendisplay the data portion consistent with the child safety setting. Forinstance, the data display option may be displaying on a display of areal machine only a data portion consistent with a child safety settingsuch as “display only non-violent data.”

FIG. 18 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 18 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1802, an operation 1804, an operation 1806, and/or anoperation 1808.

Operation 1802 shows redirecting to alternative data a user may beredirected to alternative data. Continuing the example above, dataprovider engine 108 (FIG. 1A) may be in communication with Effect ofcontent acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination from datacontent determination engine 104 (FIG. 1A) post retrieval of data bydata retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data (e.g. anotherwebsite). For instance, data content provider engine 108 may receive atleast one redirect instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a user preference stored in acopy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect instruction to thedata content provider engine 108. The data content provider engine 108may transmit the redirect data instruction to the data redirectionengine 128 for redirection to alternative data. The data redirectionengine 128 may transmit the redirection to the data content providerengine 108. Data content provider engine 108 may then display thealternative data.

Operation 1804 shows displaying alternative data consistent with aprivacy related setting. Continuing the example above, data providerengine 108 (FIG. 1A) may be in communication with Effect of contentacceptability determination engine 106 (FIG. 1A), which may receive dataand an associated data content determination from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with aprivacy related setting (e.g. another website). For instance, datacontent provider engine 108 may receive at least one redirectinstruction from at least one component of Effect of contentacceptability determination engine 106 (FIG. IA). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide a redirect instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a privacy related setting stored in a copy ofthe user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the redirect to alternative data consistentwith a privacy related setting instruction to the data content providerengine 108. The data content provider engine 108 may transmit theredirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with a privacy relatedsetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a privacy related setting may include displaying adifferent webpage including only information consistent with a privacyrelated setting such as “display only links that do not request e-mailaddresses.” Privacy related setting may be any privacy related settingdescribed above and may include any additional privacy related settings.

Further, operation 1806 shows displaying alternative data consistentwith a customized user setting. Continuing the example above, dataprovider engine 108 (FIG. 1A) may be in communication with Effect ofcontent acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination from datacontent determination engine 104 (FIG. 1A) post retrieval of data bydata retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with acustomized user setting (e.g. another website). For instance, datacontent provider engine 108 may receive at least one redirectinstruction from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide a redirect instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a customized user setting stored in a copy ofthe user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the redirect to alternative data consistentwith a customized user setting instruction to the data content providerengine 108. The data content provider engine 108 may transmit theredirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with a customized usersetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a customized user setting may include displaying adifferent webpage including only information consistent with acustomized user setting such as “display only links containing Frenchtext.” Thus, in one specific example, a webpage or website data may bedetermined to be displayable if the data satisfies a customized usersetting when the virtual machine 11, 12 and/or 13 compares the data tothe customized user setting.

Further, operation 1808 shows displaying alternative data consistentwith a desirability setting. Continuing the example above, data providerengine 108 (FIG. IA) may be in communication with Effect of contentacceptability determination engine 106 (FIG. 1A), which may receive dataand an associated data content determination from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with adesirability setting (e.g. another website). For instance, data contentprovider engine 108 may receive at least one redirect instruction fromat least one component of Effect of content acceptability determinationengine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 mayinclude one or more instruction generating modules configured to providea redirect instruction to the Effect of content acceptabilitydetermination engine 106 after a comparison of an activation of a linkto a desirability setting stored in a copy of the user preferencedatabase 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13.Effect of content acceptability determination engine 106 may communicatethe redirect to alternative data consistent with a desirability settinginstruction to the data content provider engine 108. The data contentprovider engine 108 may transmit the redirect data instruction to thedata redirection engine 128 for redirection to alternative dataconsistent with a desirability setting. The data redirection engine 128may transmit the redirection to the data content provider engine 108.Data content provider engine 108 may then display the alternative data.Displaying alternative data consistent with a desirability setting mayinclude displaying a different webpage including only informationconsistent with a desirability setting such as “display only linkscontaining information relating to art.” Desirability setting may be anydesirability setting described above and may include any additionaldesirability settings.

FIG. 19 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 19 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 1902, and/or an operation 1904.

Operation 1902 shows displaying alternative data consistent with aworkplace established setting. Continuing the example above, dataprovider engine 108 (FIG. 1A) may be in communication with Effect ofcontent acceptability determination engine 106 (FIG. 1A), which mayreceive data and an associated data content determination from datacontent determination engine 104 (FIG. 1A) post retrieval of data bydata retriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with aworkplace established setting (e.g. another website). For instance, datacontent provider engine 108 may receive at least one redirectinstruction from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide a redirect instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a workplace established setting stored in a copyof the user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the redirect to alternative data consistentwith a workplace established setting instruction to the data contentprovider engine 108. The data content provider engine 108 may transmitthe redirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with a workplace establishedsetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a workplace established setting may include displaying adifferent webpage including only information consistent with a workplaceestablished setting such as “do not display links to social networkingwebsites.”

Operation 1904 shows displaying alternative data consistent with a userhistory setting. Continuing the example above, data provider engine 108(FIG. 1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of redirecting toalternative data consistent with a user history setting (e.g. anotherwebsite). For instance, data content provider engine 108 may receive atleast one redirect instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a user history setting storedin a copy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect to alternativedata consistent with a user history setting instruction to the datacontent provider engine 108. The data content provider engine 108 maytransmit the redirect data instruction to the data redirection engine128 for redirection to alternative data consistent with a user historysetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. For instance, displayedalternative data may be consistent with a user history such as havingviewed only music related data and pages.

FIG. 20 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 20 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 2002, an operation 2004, and/or an operation 2006.

Operation 2002 shows displaying alternative data consistent with asafety setting. Continuing the example above, data provider engine 108(FIG. 1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of redirecting toalternative data consistent with a safety setting (e.g. anotherwebsite). For instance, data content provider engine 108 may receive atleast one redirect instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a safety setting stored in acopy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect to alternativedata consistent with a safety setting instruction to the data contentprovider engine 108. The data content provider engine 108 may transmitthe redirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with a safety setting. Thedata redirection engine 128 may transmit the redirection to the datacontent provider engine 108. Data content provider engine 108 may thendisplay the alternative data. Displaying alternative data consistentwith a safety setting may include displaying a different webpageincluding only information consistent with a safety setting such as “donot display links requesting credit card information.”

Operation 2004 shows displaying alternative data consistent with aworkplace safety setting. Continuing the example above, data providerengine 108 (FIG. 1A) may be in communication with Effect of contentacceptability determination engine 106 (FIG. 1A), which may receive dataand an associated data content determination from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with aworkplace safety setting (e.g. another website). For instance, datacontent provider engine 108 may receive at least one redirectinstruction from at least one component of Effect of contentacceptability determination engine 106 (FIG. 1A). Each of virtualmachines 11, 12 and/or 13 may include one or more instruction generatingmodules configured to provide a redirect instruction to the Effect ofcontent acceptability determination engine 106 after a comparison of anactivation of a link to a workplace safety setting stored in a copy ofthe user preference database 120 (FIG. 1A) spawned on the virtualmachine 11, 12 and/or 13. Effect of content acceptability determinationengine 106 may communicate the redirect to alternative data consistentwith a workplace safety setting instruction to the data content providerengine 108. The data content provider engine 108 may transmit theredirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with a workplace safetysetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a workplace safety setting may include displaying adifferent webpage including only information consistent with a workplacesafety setting such as “do not display links requesting information onthis computer.”

Operation 2006 shows displaying alternative data consistent with a childsafety setting. Continuing the example above, data provider engine 108(FIG. 1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of redirecting toalternative data consistent with a child safety setting (e.g. anotherwebsite). For instance, data content provider engine 108 may receive atleast one redirect instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a child safety setting storedin a copy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect to alternativedata consistent with a child safety setting instruction to the datacontent provider engine 108. The data content provider engine 108 maytransmit the redirect data instruction to the data redirection engine128 for redirection to alternative data consistent with a child safetysetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a child safety setting may include displaying adifferent webpage including only information consistent with a childsafety setting such as “do not display links containing trailers forrated ‘R’ movies.”

FIG. 21 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 21 illustrates example embodiments where theproviding at least one data display option operation 240 may include atleast one additional operation. Additional operations may include anoperation 2102, an operation 2104, an operation 2106, and/or anoperation 2108.

Operation 2102 shows displaying alternative data consistent with apublic safety setting. Continuing the example above, data providerengine 108 (FIG. 1A) may be in communication with Effect of contentacceptability determination engine 106 (FIG. 1A), which may receive dataand an associated data content determination from data contentdetermination engine 104 (FIG. 1A) post retrieval of data by dataretriever engine 102 (FIG. 1A). Effect of content acceptabilitydetermination engine 106 may transfer effect of content acceptabilitydetermination to the data provider engine 108 to provide the datadisplay option of redirecting to alternative data consistent with apublic safety setting (e.g. another website). For instance, data contentprovider engine 108 may receive at least one redirect instruction fromat least one component of Effect of content acceptability determinationengine 106 (FIG. 1A). Each of virtual machines 11, 12 and/or 13 mayinclude one or more instruction generating modules configured to providea redirect instruction to the Effect of content acceptabilitydetermination engine 106 after a comparison of an activation of a linkto a public safety setting stored in a copy of the user preferencedatabase 120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13.Effect of content acceptability determination engine 106 may communicatethe redirect to alternative data consistent with a public safety settinginstruction to the data content provider engine 108. The data contentprovider engine 108 may transmit the redirect data instruction to thedata redirection engine 128 for redirection to alternative dataconsistent with a public safety setting. The data redirection engine 128may transmit the redirection to the data content provider engine 108.Data content provider engine 108 may then display the alternative data.Displaying alternative data consistent with a public safety setting mayinclude displaying a different webpage including only informationconsistent with a public safety setting such as “display onlynon-confidential data.” Public safety setting may include atransmittable information safety setting, a viewable information safetysetting and a receivable information safety setting. Transmittable orviewable information may be private user information, such as creditcard numbers, bank accounts, personal identification information or anyother personal user information. Receivable information may be anyinformation such as text, images, a virus, spyware, or any otherinformation that a user's real machine may be capable of receiving froman external source.

Operation 2104 shows displaying alternative data consistent with a homesafety setting. Continuing the example above, data provider engine 108(FIG. 1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of redirecting toalternative data consistent with a home safety setting (e.g. anotherwebsite). For instance, data content provider engine 108 may receive atleast one redirect instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a home safety setting stored ina copy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect to alternativedata consistent with a home safety setting instruction to the datacontent provider engine 108. The data content provider engine 108 maytransmit the redirect data instruction to the data redirection engine128 for redirection to alternative data consistent with a home safetysetting. The data redirection engine 128 may transmit the redirection tothe data content provider engine 108. Data content provider engine 108may then display the alternative data. Displaying alternative dataconsistent with a home safety setting may include displaying a differentwebpage including only information consistent with a home safety settingsuch as “do not display links requesting address information.”

Operation 2106 shows automatically redirecting to alternative data.Continuing the example above, data provider engine 108 (FIG. 1A) may bein communication with Effect of content acceptability determinationengine 106 (FIG. 1A), which may receive data and an associated datacontent determination from data content determination engine 104 (FIG.1A) post retrieval of data by data retriever engine 102 (FIG. 1A).Effect of content acceptability determination engine 106 may transfereffect of content acceptability determination to the data providerengine 108 to provide the data display option of redirecting toalternative data (e.g. another website) consistent with a userpreference. For instance, data content provider engine 108 may receiveat least one redirect instruction from at least one component of Effectof content acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to provide a redirect instruction to theEffect of content acceptability determination engine 106 after acomparison of an activation of a link to a user preference stored in acopy of the user preference database 120 (FIG. 1A) spawned on thevirtual machine 11, 12 and/or 13. Effect of content acceptabilitydetermination engine 106 may communicate the redirect to alternativedata consistent with the user preference instruction to the data contentprovider engine 108. The data content provider engine 108 may transmitthe redirect data instruction to the data redirection engine 128 forredirection to alternative data consistent with the user preference. Thedata redirection engine 128 may transmit the redirection to the datacontent provider engine 108. Data content provider engine 108 may thenautomatically (e.g. prior to alerting a user) display the alternativedata. For instance, a real machine 130 may be automatically redirectedto an acceptable web link, or a page of acceptable data.

Further, operation 2108 shows providing a list of selectable alternativedata options. Continuing the example above, data provider engine 108(FIG. 1A) may be in communication with Effect of content acceptabilitydetermination engine 106 (FIG. 1A), which may receive data and anassociated data content determination from data content determinationengine 104 (FIG. 1A) post retrieval of data by data retriever engine 102(FIG. 1A). Effect of content acceptability determination engine 106 maytransfer effect of content acceptability determination to the dataprovider engine 108 to provide the data display option of providing alist of selectable alternative data options (e.g. a list of alternativewebsites) consistent with a user preference. For instance, data contentprovider engine 108 may receive at least one provide selectablealternatives instruction from at least one component of Effect ofcontent acceptability determination engine 106 (FIG. 1A). Each ofvirtual machines 11, 12 and/or 13 may include one or more instructiongenerating modules configured to transmit a provide selectablealternatives instruction to the Effect of content acceptabilitydetermination engine 106 after a comparison of an activation of a linkto a user preference stored in a copy of the user preference database120 (FIG. 1A) spawned on the virtual machine 11, 12 and/or 13. Effect ofcontent acceptability determination engine 106 may communicate theprovide selectable alternatives instruction to the data content providerengine 108. The data content provider engine 108 may transmit theprovide selectable alternatives instruction to the data redirectionengine 128 to provide selectable alternatives consistent with the userpreference. The data redirection engine 128 may transmit the list ofselectable alternatives to the data content provider engine 108. Datacontent provider engine 108 may then display the list of selectablealternatives. For instance, the list of selectable alternative dataoptions may include a list of acceptable web links or a selectable listof web pages. Selectable web links and web pages may include a thumbnailimage of the first page of the web link or of the web page.

FIG. 22 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 22 illustrates example embodiments where theproviding at least one data display option operation 230 may include atleast one additional operation. Additional operations may include anoperation 2202, an operation 2204, an operation 2206, and/or anoperation 2208.

At the operation 2202, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation includes determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of the content of the real machine.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106. Effect of content acceptabilitydetermination engine 106 may receive a data content determination fromdata content determination engine 104 post retrieval of data by dataretriever engine 102. FIG. 1A further illustrates the Effect of contentacceptability determination engine 106 further including a virtualmachine module 118 and a user preference database 120. Virtual machinemodule 118 includes virtual machines 11, 12 and/or 13. Effect of contentacceptability determination engine 106 may transfer data received fromdata content determination engine 104 following a determination of datacontent. Effect of content acceptability determination engine 106 maytransfer the data and associated data content determination to thevirtual machine module 118. Virtual machine module 118 (FIG. 1A) mayspawn at least one virtual machine 11, 12, and/or 13 and transfer thedata and associated data content determination to at least one ofvirtual machines 11, 12 and/or 13. FIG. 1B shows virtual machines 11, 12and/or 13 encompassing a virtual machine representation of real machine130, post (e.g. subsequent to) activation of Link 1, Link 2, and Link 3,respectively (e.g., as at least a part of real machine 130 would existhad link 1, link 2, and/or link 3 actually been traversed on realmachine 130). FIG. 1B further depicts virtual machines 11, 12 and/or 13including a virtual machine representation of content of the realmachine 130 post activation of Link 1, Link 2, and/or Link 3,respectively. Examples of such content include a movie, music file, ascript (e.g., Java script or Active X control), a markup language, anemail, etc. downloaded onto real machine 130 from one or more sourcesassociated with activation/traversal of Link 1, Link 2, and/or Link 3.An example of determining an acceptability of an effect of the contentof the data at least in part via a virtual machine representation mayinclude determining an acceptability of an effect of the content of thedata at least in part via a virtual machine representation of at least aportion of the content of the real machine include determining whetheror not a video or image has been loaded onto, for example, the virtualmachine 11 after loading at least a portion of the data contained inLink 1.

Determining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation includes determiningan acceptability of an effect of the content of the data at least inpart via a virtual machine representation of at least a portion of thecontent of the real machine may also include determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation includes determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of thecontent of the real machine on a virtual machine representation of atleast a portion of a real machine generated by, for example, virtualmachine 11. FIG. 1C shows a partial follow-on operational view of realmachine 130 (e.g., a desktop, notebook, or other type computing system)in which at least a portion of system 100 (FIG. 1A) has been implemented(e.g., a follow-on operational view of the systems/methods illustratedas in FIG. 1B). Specifically, FIG. 1C shows a drill-down view of anexample of the virtual machine 11 including a virtual machinerepresentation of the content of the real machine 130 post activation ofLink 1 (e.g., a drill-down on the systems/methods shown/described inrelation to FIG. 1B). In this drill down example, depicted is thevirtual machine representation of the content of the real machine 130post activation of Link 1.

In some instances, system 100 may use additional virtual machinerepresentations of at least a part of real machine 130 to prospectivelytraverse Link 4, Link 5, and Link 6 post traversal of Link 1.Accordingly, FIG. 1C illustrates system 100 generating virtual machinerepresentations of real machine 130, used to traverse Links 4, 5, and 6,in the context of virtual machines 21, 22, and 23, respectively. Thoseskilled in the art will thus appreciate that, in the example shown inFIG. 1C, system 100 is creating second-order virtual machinerepresentations to prospectively investigate the effects on the statesof various components of real machine 130 via sequential traversals oflinks. That is, the virtual machine representations of real machine 130encompassed in virtual machine 21, virtual machine 22, and virtualmachine 23 of FIG. 1C are generated by system 100 based on thefirst-order virtual machine representation of virtual machine 11 asshown/described in relation to FIG. 1B.

FIG. 1C shows virtual machine 21 encompassing a virtual machinerepresentation of real machine 130 post (e.g. subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 4(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 21 may be run on core 31 of a multi-core processor. FIG.1C depicts system 100 traversing Links 4, 5, and/or 6 via a virtualmachine representation of real machine 130 encompassed within virtualmachines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtualmachine 21 including a virtual machine representation of content (e.g.,a movie, web page, music file, etc.) of the real machine 130 postsequential activation of Link 1 then Link 4, virtual machine 22including a virtual machine representation of content (e.g. a graphicalimage, a text file, an email, etc) of the real machine 130 post (e.g.,subsequent to) sequential activation of Link 1 then Link 5, and virtualmachine 23 encompassing a virtual machine representation of the content(e.g. a music file) of the real machine 130 post sequential activationof Link 1 then Link 6. A determination of an acceptability of an effectof the content of data on the content of the real machine made onvirtual machine 21 may include determining whether or not an audio filehas been loaded onto virtual machine 21. Virtual machine 21 maycommunicate a determination of an acceptability of an effect of thecontent of data determination made on a virtual machine 21 which may beat least a portion of content of the real machine to virtual machine 11,which may communicate the acceptability of an effect of the content ofdata determination to the virtual machine module 118 (FIG. 1A) forcommunication to the Effect of content acceptability determinationengine 106 (FIG. 1A).

At the operation 2204, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation includes determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of the software of the realmachine. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102. FIG. 1A further illustrates theEffect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B shows virtual machines 11, 12 and/or 13 encompassing avirtual machine representation of real machine 130, post (e.g.subsequent to) activation of Link 1, Link 2, and Link 3, respectively(e.g., as at least a part of real machine 130 would exist had link 1,link 2, and/or link 3 actually been traversed on real machine 130). FIG.1B illustrates virtual machine 11 including a virtual machinerepresentation of software (e.g., a state of software) of the realmachine 130 post (e.g. subsequent to) activation of Link 1. Examples ofsuch software might include a commercial word processing program orsuite of programs (e.g. Microsoft® Office for Windows), an open sourceWeb browser (e.g., Mozilla's Firefox® Browser), an AJAX mash up (e.g.,an executing JavaScript™ and/or data retrieved by same via an XML-likescheme), or a commercial database management system (e.g., one or moreof Oracle Corporation's various products), a commercialanti-malware/spyware programs (e.g., such as those of SymantecCorporation or McAfee,Inc.), etc. An example of determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation may include determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of thesoftware of the real machine include determining whether or not anunauthorized program or suite of programs (e.g. music downloadingsoftware) has been loaded, for example, onto virtual machine 12 afterloading at least a portion of the data contained in Link 2.

Determining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation includes determiningan acceptability of an effect of the content of the data at least inpart via a virtual machine representation of at least a portion of thesoftware of the real machine may also include determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation includes determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of thesoftware of the real machine on a virtual machine representation of atleast a portion of the software of a real machine generated by, forexample, virtual machine 11. FIG. 1C shows a partial follow-onoperational view of real machine 130 (e.g., a desktop, notebook, orother type computing system) in which at least a portion of system 100(FIG. 1A) has been implemented (e.g., a follow-on operational view ofthe systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1Cshows a drill-down view of an example of the virtual machine 11including a virtual machine representation of the content of the realmachine 130 post activation of Link 1 (e.g., a drill-down on thesystems/methods shown/described in relation to FIG. 1B). In this drilldown example, depicted is the virtual machine representation of thecontent of the real machine 130 post activation of Link 1.

In some instances, system 100 may use additional virtual machinerepresentations of at least a part of real machine 130 to prospectivelytraverse Link 4, Link 5, and Link 6. Accordingly, FIG. 1C illustratessystem 100 generating virtual machine representations of real machine130, used to traverse Links 4, 5, and 6, in the context of virtualmachines 21, 22, and 23, respectively. Those skilled in the art willthus appreciate that, in the example shown in FIG. 1C, system 100 iscreating second-order virtual machine representations to prospectivelyinvestigate the effects on the states of various components of realmachine 130 via sequential traversals of links. That is, the virtualmachine representations of real machine 130 encompassed in virtualmachine 21, virtual machine 22, and virtual machine 23 of FIG. 1C aregenerated by system 100 based on the first-order virtual machinerepresentation of virtual machine 11 as shown/described in relation toFIG. 1B.

FIG. 1C shows virtual machine 21 encompassing a virtual machinerepresentation of real machine 130 post (e.g. subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 4(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 21 may be run on core 31 of a multi-core processor. FIG.1C depicts system 100 traversing Links 4, 5, and/or 6 via a virtualmachine representation of real machine 130 encompassed within virtualmachines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtualmachine 21 including a virtual machine representation of the software(e.g.) of the real machine 130 post sequential activation of Link 1 thenLink 4, virtual machine 22 including a virtual machine representation ofsoftware (e.g. an AJAX mashup) of the real machine 130 post sequentialactivation of Link 1 then Link 5, and a virtual machine representationof the software (e.g. a commercial database management system) of thereal machine 130 post sequential activation of Link 1 then Link 6. Adetermination of an acceptability of an effect of the content of data onthe software of the real machine made on virtual machine 21 may includedetermining whether or not malware or grayware has been loaded ontovirtual machine 21. Virtual machine 21 may communicate a determinationof acceptability of an effect of the content of data on a virtualmachine representation of at least a portion of software of the realmachine made on virtual machine 21 to virtual machine 11, which maycommunicate the acceptability of an effect of the content of datadetermination to the virtual machine module 118 (FIG. 1A) forcommunication to the Effect of content acceptability determinationengine 106 (FIG. 1A).

At the operation 2206, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation includes determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of the hardware of the realmachine. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102. FIG. 1A further illustrates theEffect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B shows virtual machines 11, 12 and/or 13 encompassing avirtual machine representation of real machine 130, post (e.g.subsequent to) activation of Link 1, Link 2, and Link 3, respectively(e.g., as at least a part of real machine 130 would exist had link 1,link 2 or link 3 actually been traversed on real machine 130). FIG. 1Billustrates virtual machine 11 including a virtual machinerepresentation of hardware (e.g. a state of the hardware) of the realmachine 130 post activation of Link 1. Examples of such hardware mightinclude all or part of a chipset (e.g., data processor and/or graphicsprocessor chipsets such as those of Intel Corporation and/orNvidiaCorporation), a memory chip (e.g., flash memory and/or randomaccess memories such as those of Sandisk Corporation and/or SamsungElectronics, Co., LTD), a data bus, a hard disk (e.g., such as those ofSeagate Technology, LLC), a network adapter (e.g., wireless and/or wiredLAN adapters such as those of Linksys and/or CiscoTechnology, Inc.),printer, a removable drive (e.g., flash drive), a cell phone, etc. Anexample of determining an acceptability of an effect of the content ofthe data at least in part via a virtual machine representation includesdetermining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation of at least a portionof the hardware of the real machine include determining whether anetwork adapter on, for example, virtual machine 12 has been disabledafter loading at least a portion of the data contained in Link 2.

Determining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation includes determiningan acceptability of an effect of the content of the data at least inpart via a virtual machine representation of at least a portion of thehardware of the real machine may also include determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation includes determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of thehardware of the real machine on a virtual machine representation of atleast a portion of the hardware of a real machine generated by, forexample, virtual machine 11. FIG. 1C shows a partial follow-onoperational view of real machine 130 (e.g., a desktop, notebook, orother type computing system) in which at least a portion of system 100(FIG. 1A) has been implemented (e.g., a follow-on operational view ofthe systems/methods illustrated as in FIG. 1B). Specifically, FIG. 1Cshows a drill-down view of an example of the virtual machine 11including a virtual machine representation of the content of the realmachine 130 post activation of Link 1 (e.g., a drill-down on thesystems/methods shown/described in relation to FIG. 1B). In this drilldown example, depicted is the virtual machine representation of thecontent of the real machine 130 post activation of Link 1.

In some instances, system 100 may use additional virtual machinerepresentations of at least a part of real machine 130 to prospectivelytraverse Link 4, Link 5, and Link 6. Accordingly, FIG. 1C illustratessystem 100 generating virtual machine representations of real machine130, used to traverse Links 4, 5, and 6, in the context of virtualmachines 21, 22, and 23, respectively. Those skilled in the art willthus appreciate that, in the example shown in FIG. 1C, system 100 iscreating second-order virtual machine representations to prospectivelyinvestigate the effects on the states of various components of realmachine 130 via sequential traversals of links. That is, the virtualmachine representations of real machine 130 encompassed in virtualmachine 21, virtual machine 22, and virtual machine 23 of FIG. 1C aregenerated by system 100 based on the first-order virtual machinerepresentation of virtual machine 11 as shown/described in relation toFIG. 1B.

FIG. 1C shows virtual machine 21 encompassing a virtual machinerepresentation of real machine 130 post (e.g. subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 4(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 21 may be run on core 31 of a multi-core processor. FIG.1C depicts system 100 traversing Links 4, 5, and/or 6 via a virtualmachine representation of real machine 130 encompassed within virtualmachines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtualmachine 21 including a virtual machine representation of the hardware(e.g. the circuitry or processor of the real machine) of the realmachine 130 post sequential activation of Link 1 then Link 4, a virtualmachine representation of hardware (e.g. a network adapter) of the realmachine 130 post sequential activation of Link 1 then Link 5, and avirtual machine representation of the hardware (e.g. a removable drive)of the real machine 130 post sequential activation of Link 1 then Link6. A determination of an acceptability of an effect of the content ofdata on the hardware of the real machine made on virtual machine 21 mayinclude determining whether a decrease in processor speed of virtualmachine 21 has occurred. Virtual machine 21 may communicate adetermination of acceptability of an effect of the content of data on avirtual machine representation of at least a portion of hardware of thereal machine made on virtual machine 21 to virtual machine 11, which maycommunicate the acceptability of an effect of the content of datadetermination to the virtual machine module 118 (FIG. 1A) forcommunication to the Effect of content acceptability determinationengine 106 (FIG. 1A).

At the operation 2208, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation includes determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of the operating system of the realmachine. Continuing the example above, FIG. 1A shows the Effect ofcontent acceptability determination engine 106. Effect of contentacceptability determination engine 106 may receive a data contentdetermination from data content determination engine 104 post retrievalof data by data retriever engine 102. FIG. 1A further illustrates theEffect of content acceptability determination engine 106 furtherincluding a virtual machine module 118 and a user preference database120. Virtual machine module 118 includes virtual machines 11, 12 and/or13. Effect of content acceptability determination engine 106 maytransfer data received from data content determination engine 104following a determination of data content. Effect of contentacceptability determination engine 106 may transfer the data andassociated data content determination to the virtual machine module 118.Virtual machine module 118 (FIG. 1A) may spawn at least one virtualmachine 11, 12, and/or 13 and transfer the data and associated datacontent determination to at least one of virtual machines 11, 12 and/or13. FIG. 1B shows virtual machines 11, 12 and/or 13 encompassing avirtual machine representation of real machine 130, post (e.g.subsequent to) activation of Link 1, Link 2, and Link 3, respectively(e.g., as at least a part of real machine 130 would exist had link 1,link 2, and/or link 3 actually been traversed on real machine 130). FIG.1B also illustrates virtual machine 11 including a virtual machinerepresentation of an operating system (e.g., a state of an operatingsystem and/or network operating system) of the real machine 130 postactivation of Link 1. Examples of such an operating system might includea computer operating system (e.g., e.g. Microsoft® Windows 2000, Unix,Linux, etc) and/or a network operating system (e.g., the InternetOperating System available from Cisco Technology, Inc. Netware®available from Novell, Inc., and/or Solaris available from SunMicrosystems, Inc.). An example of determining an acceptability of aneffect of the content of the data at least in part via a virtual machinerepresentation includes determining an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of an operating system of the realmachine include determining whether a portion of the operating system(e.g. Microsft Vista) on for example, virtual machine 12 has beendisabled after loading at least a portion of the data contained in Link2.

Determining an acceptability of an effect of the content of the data atleast in part via a virtual machine representation includes determiningan acceptability of an effect of the content of the data at least inpart via a virtual machine representation of at least a portion of theoperating system of the real machine may also include determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation includes determining anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of theoperating system of the real machine on a virtual machine representationof at least a portion of the operating system of a real machinegenerated by, for example, virtual machine 11. FIG. 1C shows a partialfollow-on operational view of real machine 130 (e.g., a desktop,notebook, or other type computing system) in which at least a portion ofsystem 100 (FIG. 1A) has been implemented (e.g., a follow-on operationalview of the systems/methods illustrated as in FIG. 1B). Specifically,FIG. 1C shows a drill-down view of an example of the virtual machine 11including a virtual machine representation of the content of the realmachine 130 post activation of Link 1 (e.g., a drill-down on thesystems/methods shown/described in relation to FIG. 1B). In this drilldown example, depicted is the virtual machine representation of thecontent of the real machine 130 post activation of Link 1.

In some instances, system 100 may use additional virtual machinerepresentations of at least a part of real machine 130 to prospectivelytraverse Link 4, Link 5, and Link 6. Accordingly, FIG. 1C illustratessystem 100 generating virtual machine representations of real machine130, used to traverse Links 4, 5, and 6, in the context of virtualmachines 21, 22, and 23, respectively. Those skilled in the art willthus appreciate that, in the example shown in FIG. 1C, system 100 iscreating second-order virtual machine representations to prospectivelyinvestigate the effects on the states of various components of realmachine 130 via sequential traversals of links. That is, the virtualmachine representations of real machine 130 encompassed in virtualmachine 21, virtual machine 22, and virtual machine 23 of FIG. 1C aregenerated by system 100 based on the first-order virtual machinerepresentation of virtual machine 11 as shown/described in relation toFIG. 1B.

FIG. 1C shows virtual machine 21 encompassing a virtual machinerepresentation of real machine 130 post (e.g. subsequent to) asequential activation of Link 1 (e.g., as shown on FIG. 1B) then Link 4(e.g., as shown on FIG. 1C). FIG. 1C depicts that in one instancevirtual machine 21 may be run on core 31 of a multi-core processor. FIG.1C depicts system 100 traversing Links 4, 5, and/or 6 via a virtualmachine representation of real machine 130 encompassed within virtualmachines 21, 22 and/or 23. Accordingly, FIG. 1C illustrates virtualmachine 21 including a virtual machine representation of the operatingsystem (e.g. Linux) of the real machine 130 post sequential activationof Link 1 then Link 4, a virtual machine representation of an operatingsystem (e.g. Mac OS/X) of the real machine 130 post sequentialactivation of Link 1 then Link 5, and a virtual machine representationof the operating system (e.g. GNU, Berkeley Software Distribution) ofthe real machine 130 post sequential activation of Link 1 then Link 6(e.g., as such might appear after activation of a link installed by arootkit via malware/spyware). A determination of an acceptability of aneffect of the content of data on the operating system of the realmachine made on virtual machine 21 may include determining whether ornot a rootkit has been installed onto virtual machine 21. Virtualmachine 21 may communicate a determination of acceptability of an effectof the content of data on a virtual machine representation of at least aportion of operating system of the real machine made on virtual machine21 to virtual machine 11, which may communicate the acceptability of aneffect of the content of data determination to the virtual machinemodule 118 (FIG. 1A) for communication to the Effect of contentacceptability determination engine 106 (FIG. 1A).

FIG. 23 illustrates alternative embodiments of the example operationalflow 200 of FIG. 2. FIG. 23 illustrates example embodiments where theproviding at least one data display option operation 230 may include atleast one additional operation. Additional operations may include anoperation 2302, an operation 2304, and/or an operation 2306.

At the operation 2302, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences includes determining an acceptability ofan effect of the content of the data at least in part via a virtualmachine representation of at least a part of a real machine including atleast a part of a computing device. FIG. 1D illustrates real machine 130including at least a part of a computing device 132. The computingdevice 132 may be any device capable of processing one or moreprogramming instructions. For example, the computing device 132 may be adesktop computer, a laptop computer, a notebook computer, a mobilephone, a personal digital assistant (PDA), combinations thereof, and/orother suitable computing devices.

At the operation 2304, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences includes determining an acceptability ofan effect of the content of the data at least in part via a virtualmachine representation of at least a part of a real machine including atleast one peripheral device. Continuing the example above, FIG. 1A showsthe Effect of content acceptability determination engine 106. Effect ofcontent acceptability determination engine 106 may receive a datacontent determination from data content determination engine 104 postretrieval of data by data retriever engine 102 and communication ofretrieved data to data content determination engine 104. FIG. 1A furtherillustrates the Effect of content acceptability determination engine 106further including a virtual machine module 118 and a user preferencedatabase 120. Virtual machine module 118 may spawn virtual machines 11,12 and/or 13 that may be virtual machine representations of at least apart of real machine 130. Real machine 130 may include at least oneperipheral device. For instance, FIG. 1D illustrates real machine 130including at least one peripheral device 134-146. FIG. 1D shows arepresentative view of an implementation of real machine 130 (e.g., adesktop, notebook, or other type computing system, and/or one or moreperipheral devices) in which all/part of system 100 may be implemented.FIG. 1D illustrates that implementations of real machine 130 may includeall/part of computing device 132 and/or all/part of one or one or moreperipherals associated computing device 132.

At the operation 2306, the determining an acceptability of an effect ofthe content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences includes determining an acceptability ofan effect of the content of the data at least in part via a virtualmachine representation of at least a part of a real machine including atleast one peripheral device includes determining an acceptability of aneffect of the content of the data at least in part via a virtual machinerepresentation of at least a part of a real machine having one or moreend-user specified preferences includes determining an acceptability ofan effect of the content of the data at least in part via a virtualmachine representation of at least a part of a real machine including atleast one peripheral device that is at least one of a printer, a faxmachine, a peripheral memory device, a network adapter, a music player,a cellular telephone, a data acquisition device, or a device actuator.Continuing the example above, FIG. 1A shows the Effect of contentacceptability determination engine 106. Effect of content acceptabilitydetermination engine 106 may receive a data content determination fromdata content determination engine 104 post retrieval of data by dataretriever engine 102 and communication of retrieved data to data contentdetermination engine 104. FIG. 1A further illustrates the Effect ofcontent acceptability determination engine 106 further including avirtual machine module 118 and a user preference database 120. Virtualmachine module 118 may spawn virtual machines 11, 12 and/or 13 that maybe virtual machine representations of at least a part of real machine130. Real machine 130 may include at least one peripheral device. Forinstance, FIG. 1D illustrates a real machine may also include at least aportion of one or more peripheral devices connected/connectable (e.g.,via wired, waveguide, or wireless connections) to real machine 130.Peripheral devices may include one or more printers 134, one or more faxmachines 136, one or more peripheral memory devices 138 (e.g., flashdrive, memory stick), one or more network adapters 139 (e.g., wired orwireless network adapters), one or more music players 140, one or morecellular telephones 142, one or more data acquisition devices 144 (e.g.robots) and/or one or more device actuators 146 (e.g., an hydraulic arm,a radiation emitter, or any other component(s) of industrial/medicalsystems).

Those having skill in the art will recognize that the state of the arthas progressed to the point where there is little distinction leftbetween hardware and software implementations of aspects of systems; theuse of hardware or software is generally (but not always, in that incertain contexts the choice between hardware and software can becomesignificant) a design choice representing cost vs. efficiency tradeoffs.Those having skill in the art will appreciate that there are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; alternatively, if flexibility is paramount, theimplementer may opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware. Hence, there are several possible vehicles bywhich the processes and/or devices and/or other technologies describedherein may be effected, none of which is inherently superior to theother in that any vehicle to be utilized is a choice dependent upon thecontext in which the vehicle will be deployed and the specific concerns(e.g., speed, flexibility, or predictability) of the implementer, any ofwhich may vary. Those skilled in the art will recognize that opticalaspects of implementations will typically employ optically-orientedhardware, software, and or firmware.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, those skilled in the art willrecognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure. In addition, those skilled in the art will appreciatethat the mechanisms of the subject matter described herein are capableof being distributed as a program product in a variety of forms, andthat an illustrative embodiment of the subject matter described hereinapplies regardless of the particular type of signal bearing medium usedto actually carry out the distribution. Examples of a signal bearingmedium include, but are not limited to, the following: a recordable typemedium such as a floppy disk, a hard disk drive, a Compact Disc (CD), aDigital Video Disk (DVD), a digital tape, a computer memory, etc.; and atransmission type medium such as a digital and/or an analogcommunication medium (e.g., a fiber optic cable, a waveguide, a wiredcommunications link, a wireless communication link, etc.).

In a general sense, those skilled in the art will recognize that thevarious aspects described herein which can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware, orany combination thereof can be viewed as being composed of various typesof “electrical circuitry.” Consequently, as used herein “electricalcircuitry” includes, but is not limited to, electrical circuitry havingat least one discrete electrical circuit, electrical circuitry having atleast one integrated circuit, electrical circuitry having at least oneapplication specific integrated circuit, electrical circuitry forming ageneral purpose computing device configured by a computer program (e.g.,a general purpose computer configured by a computer program which atleast partially carries out processes and/or devices described herein,or a microprocessor configured by a computer program which at leastpartially carries out processes and/or devices described herein),electrical circuitry forming a memory device (e.g., forms of randomaccess memory), and/or electrical circuitry forming a communicationsdevice (e.g., a modem, communications switch, or optical-electricalequipment). Those having skill in the art will recognize that thesubject matter described herein may be implemented in an analog ordigital fashion or some combination thereof.

Those skilled in the art will recognize that it is common within the artto describe devices and/or processes in the fashion set forth herein,and thereafter use engineering practices to integrate such describeddevices and/or processes into data processing systems. That is, at leasta portion of the devices and/or processes described herein can beintegrated into a data processing system via a reasonable amount ofexperimentation. Those having skill in the art will recognize that atypical data processing system generally includes one or more of asystem unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control motors (e.g., feedback forsensing position and/or velocity; control motors for moving and/oradjusting components and/or quantities). A typical data processingsystem may be implemented utilizing any suitable commercially availablecomponents, such as those typically found in datacomputing/communication and/or network computing/communication systems.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures can beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected”, or“operably coupled”, to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable”, to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents and/or wirelessly interactable and/or wirelessly interactingcomponents and/or logically interacting and/or logically interactablecomponents.

While particular aspects of the present subject matter described hereinhave been shown and described, it will be apparent to those skilled inthe art that, based upon the teachings herein, changes and modificationsmay be made without departing from the subject matter described hereinand its broader aspects and, therefore, the appended claims are toencompass within their scope all such changes and modifications as arewithin the true spirit and scope of the subject matter described herein.Furthermore, it is to be understood that the invention is defined by theappended claims. It will be understood by those within the art that, ingeneral, terms used herein, and especially in the appended claims (e.g.,bodies of the appended claims) are generally intended as “open” terms(e.g., the term “including” should be interpreted as “including but notlimited to,” the term “having” should be interpreted as “having atleast,” the term “includes” should be interpreted as “includes but isnot limited to,” etc.). It will be further understood by those withinthe art that if a specific number of an introduced claim recitation isintended, such an intent will be explicitly recited in the claim, and inthe absence of such recitation no such intent is present. For example,as an aid to understanding, the following appended claims may containusage of the introductory phrases “at least one” and “one or more” tointroduce claim recitations. However, the use of such phrases should notbe construed to imply that the introduction of a claim recitation by theindefinite articles “a” or “an” limits any particular claim containingsuch introduced claim recitation to inventions containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations. In addition, evenif a specific number of an introduced claim recitation is explicitlyrecited, those skilled in the art will recognize that such recitationshould typically be interpreted to mean at least the recited number(e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations). Furthermore, in those instances where a conventionanalogous to “at least one of A, B, and C, etc.” is used, in generalsuch a construction is intended in the sense one having skill in the artwould understand the convention (e.g., “a system having at least one ofA, B, and C” would include but not be limited to systems that have Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). In those instances where aconvention analogous to “at least one of A, B, or C, etc.” is used, ingeneral such a construction is intended in the sense one having skill inthe art would understand the convention (e.g., “a system having at leastone of A, B, or C” would include but not be limited to systems that haveA alone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). It will be furtherunderstood by those within the art that virtually any disjunctive wordand/or phrase presenting two or more alternative terms, whether in thedescription, claims, or drawings, should be understood to contemplatethe possibilities of including one of the terms, either of the terms, orboth terms. For example, the phrase “A or B” will be understood toinclude the possibilities of “A” or “B” or “A and B.”

The invention claimed is:
 1. A system comprising: a data retrieverengine configured to retrieve data content; a data content determinationengine configured to provide a virtual machine representation of atleast one piece of hardware of an end user's real machine had the datacontent been received by the end user's real machine; an effect ofcontent acceptability determination engine including circuitryconfigured to determine an acceptability of an effect of the datacontent at least in part via a comparison of at least one changeresulting from the data content interacting with the virtual machinerepresentation against at least one end-user specified preference of theend-user's real machine; and a data provider engine including circuitryconfigured to provide at least one option to the end-user's real machinebased on a determination of an acceptability of an effect of the datacontent.
 2. The system of claim 1, wherein the data contentdetermination engine comprises: a database examination engine.
 3. Thesystem of claim 1, wherein the data content determination enginecomprises: a data traverser engine.
 4. The system of claim 1, whereinthe data content determination engine comprises: a local dataexamination engine.
 5. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: a user preferencedatabase.
 6. The system of claim 1, wherein the at least one end-userspecified preference of the end user's real machine includes: at leastone user-associated preference relating to content of an end user's realmachine.
 7. The system of claim 1, wherein the at least one end-userspecified preference of the end user's real machine includes: at leastone user-associated preference relating to software of an end user'sreal machine.
 8. The system of claim 1, wherein the at least oneend-user specified preference of the end user's real machine includes:at least one user-associated preference relating to hardware of an enduser's real machine.
 9. The system of claim 1, wherein the at least oneend-user specified preference of the end user's real machine includes:at least one user-associated preference relating to an operating systemof an end user's real machine.
 10. The system of claim 1, wherein theeffect of content acceptability determination engine comprises: avirtual machine module.
 11. The system of claim 10, wherein the virtualmachine module comprises: a plurality of virtual machines.
 12. Thesystem of claim 11, wherein the virtual machine module comprises:circuitry configured to spawn a copy of at least a portion of the userpreference database on at least one of the plurality of virtualmachines.
 13. The system of claim 10, wherein the virtual machine modulecomprises: circuitry configured to compare at least one user-associatedpreference from a user preference database to a retrieved data portion.14. The system of claim 1, wherein the data retriever engine comprises:circuitry configured to retrieve at least a portion of data from a datasource.
 15. The system of claim 14, wherein the at least a portion ofthe data content comprises: at least one of a web page or a web linkincluding at least a portion of a textual representation, atwo-dimensional image, a three-dimensional image, an audio file, or avideo representation.
 16. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data on at least two virtual machine representations of at least apart of an end user's real machine having one or more end-user specifiedpreferences.
 17. The system of claim 1, wherein the effect of contentacceptability determination engine comprises: circuitry configured todetermine an acceptability of an effect of the content of the data on atleast two virtual machine representations of at least a part of an enduser's real machine having one or more end-user specified preferences atleast one of the at least two virtual machine representations operatingon a separate operating system.
 18. The system of claim 1, wherein theeffect of content acceptability determination engine comprises:circuitry configured to determine an acceptability of an effect of thecontent of the data on at least two virtual machine representations ofat least a part of an end user's real machine having one or moreend-user specified preferences, at least one of the at least two virtualmachine representations operating on a separate core of a systemincluding at least two cores.
 19. The system of claim 1, wherein theeffect of content acceptability determination engine comprises:circuitry configured to determine a state change of a virtual machinerepresentation between a prior state and a subsequent state of thevirtual machine representation after loading at least a portion of data.20. The system of claim 1, wherein the effect of content acceptabilitydetermination engine comprises: circuitry configured to determine astate of a virtual machine representation prior to loading at least aportion of data.
 21. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine a state of a virtual machine after loading atleast a portion of data.
 22. The system of claim 1, wherein the effectof content acceptability determination engine comprises: circuitryconfigured to determine whether a state change is an undesirable statechange based on one or more end-user specified preferences.
 23. Thesystem of claim 1, wherein the effect of content acceptabilitydetermination comprises: circuitry configured to determine anacceptability of an effect of the content of the data in response to atleast one user setting.
 24. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data in response to visually examining a data image.
 25. The systemof claim 1, wherein the effect of content acceptability determinationengine comprises: circuitry configured to determine an acceptability ofan effect of the content of the data at least in part via a virtualmachine representation of at least a portion of the content of an enduser's real machine.
 26. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data at least in part via a virtual machine representation of atleast a portion of software of an end user's real machine.
 27. Thesystem of claim 1, wherein the effect of content acceptabilitydetermination engine comprises: circuitry configured to determine anacceptability of an effect of the content of the data at least in partvia a virtual machine representation of at least a portion of hardwareof an end user's real machine.
 28. The system of claim 1, wherein theeffect of content acceptability determination engine comprises:circuitry configured to determine an acceptability of an effect of thecontent of the data at least in part via a virtual machinerepresentation of at least a portion of an operating system of an enduser's real machine.
 29. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data at least in part via a virtual machine representation of atleast a part of an end user's real machine including at least a portionof a computing device.
 30. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data at least in part via a virtual machine representation of atleast a part of an end user's real machine including at least oneperipheral device.
 31. The system of claim 1, wherein the effect ofcontent acceptability determination engine comprises: circuitryconfigured to determine an acceptability of an effect of the content ofthe data at least in part via a virtual machine representation of atleast a part of an end user's real machine including at least oneperipheral device that is at least one of a printer, a fax machine, aperipheral memory device, a network adapter, a music player, a cellulartelephone, a data acquisition device, or a device actuator.
 32. Thesystem of claim 1, wherein the data provider engine comprises: a datamodification engine.
 33. The system of claim 32, wherein the datamodification engine comprises: circuitry configured to display amodified version of data.
 34. The system of claim 33, wherein thecircuitry configured to display a modified version circuitry configuredto remove, alter, or replace an objectionable data portion.
 35. Thesystem of claim 33, wherein circuitry configured to display a modifiedversion of data comprises: circuitry configured to display a dataportion consistent with at least one user-associated preference.
 36. Thesystem of claim 32, wherein the data modification engine comprises: adata obfuscation engine.
 37. The system of claim 36, wherein the dataobfuscation engine comprises: circuitry configured to obfuscate dataprior to displaying data.
 38. The system of claim 37, wherein thecircuitry configured to obfuscate data prior to displaying datacomprises: circuitry configured to blur or block an objectionable dataportion.
 39. The system of claim 32, wherein the data modificationengine comprises: a data anonymization engine.
 40. The system of claim39, wherein the data anonymization engine comprises: circuitryconfigured to display an anonymized version of data.
 41. The system ofclaim 40, wherein the circuitry configured to display an anonymizedversion of data comprises: circuitry configured to hide, obscure, orreplace original identity information of the data.
 42. The system ofclaim 1, wherein the data provider engine comprises: a data redirectionengine.
 43. The system of claim 42, wherein the data redirection enginecomprises: circuitry configured to redirect a user to data consistentwith at least one userassociated preference.
 44. The system of claim 42,wherein the data redirection engine comprises: circuitry configured toautomatically redirect a user to alternative data.
 45. The system ofclaim 42, wherein the data redirection engine comprises: circuitryconfigured to provide a selectable list of one or more dataalternatives.